21,130 results on '"Gelman, A"'
Search Results
2. Adaptive sequential Monte Carlo for automated cross validation in structural Bayesian hierarchical models
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Han, Geonhee and Gelman, Andrew
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Statistics - Computation ,Statistics - Applications - Abstract
Importance sampling (IS) is widely used for approximate Bayesian cross validation (CV) due to its efficiency, requiring only the re-weighting of a single set of posterior draws. With structural Bayesian hierarchical models, vanilla IS can produce unreliable results, as out-of-sample replication may involve non-standard case-deletion schemes which significantly alter the posterior geometry. This inevitably necessitates computationally expensive re-runs of Markov chain Monte Carlo (MCMC), making structural CV impracticable. To address this challenge, we consider sampling from a sequence of posteriors leading to the case-deleted posterior(s) via adaptive sequential Monte Carlo (SMC). We design the sampler to (a) support a broad range of structural CV schemes, (b) enhance efficiency by adaptively selecting Markov kernels, intervening in parallelizable MCMC re-runs only when necessary, and (c) streamline the workflow by automating the design of intermediate bridging distributions. Its practical utility is demonstrated through three real-world applications involving three types of predictive model assessments: leave-group-out CV, group $K$-fold CV, and sequential one-step-ahead validation.
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- 2025
3. The ladder of abstraction in statistical graphics
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Gelman, Andrew
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Statistics - Methodology - Abstract
Graphical forms such as scatterplots, line plots, and histograms are so familiar that it can be easy to forget how abstract they are. As a result, we often produce graphs that are difficult to follow. We propose a strategy for graphical communication by climbing a ladder of abstraction (a term from linguistics that we borrow from Hayakawa, 1939), starting with simple plots of special cases and then at each step embedding a graph into a more general framework. We demonstrate with two examples, first graphing a set of equations related to a modeled trajectory and then graphing data from an analysis of income and voting., Comment: 11 figures
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- 2025
4. Toward an Insider Threat Education Platform: A Theoretical Literature Review
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Gelman, Haywood, Hastings, John D., Kenley, David, and Loiacono, Eleanor
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Computer Science - Cryptography and Security ,Computer Science - Artificial Intelligence ,Computer Science - Computers and Society ,Computer Science - Human-Computer Interaction ,Computer Science - Social and Information Networks ,K.4.1 ,C.2.0 ,I.2.6 ,H.5.2 ,H.1.2 - Abstract
Insider threats (InTs) within organizations are small in number but have a disproportionate ability to damage systems, information, and infrastructure. Existing InT research studies the problem from psychological, technical, and educational perspectives. Proposed theories include research on psychological indicators, machine learning, user behavioral log analysis, and educational methods to teach employees recognition and mitigation techniques. Because InTs are a human problem, training methods that address InT detection from a behavioral perspective are critical. While numerous technological and psychological theories exist on detection, prevention, and mitigation, few training methods prioritize psychological indicators. This literature review studied peer-reviewed, InT research organized by subtopic and extracted critical theories from psychological, technical, and educational disciplines. In doing so, this is the first study to comprehensively organize research across all three approaches in a manner which properly informs the development of an InT education platform., Comment: 6 pages
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- 2024
5. Safeguarding Virtual Healthcare: A Novel Attacker-Centric Model for Data Security and Privacy
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Herath, Suvineetha, Gelman, Haywood, Hastings, John, and Wang, Yong
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Computer Science - Cryptography and Security ,K.6.5 ,H.2.7 ,D.4.6 ,J.3 - Abstract
The rapid growth of remote healthcare delivery has introduced significant security and privacy risks to protected health information (PHI). Analysis of a comprehensive healthcare security breach dataset covering 2009-2023 reveals their significant prevalence and impact. This study investigates the root causes of such security incidents and introduces the Attacker-Centric Approach (ACA), a novel threat model tailored to protect PHI. ACA addresses limitations in existing threat models and regulatory frameworks by adopting a holistic attacker-focused perspective, examining threats from the viewpoint of cyber adversaries, their motivations, tactics, and potential attack vectors. Leveraging established risk management frameworks, ACA provides a multi-layered approach to threat identification, risk assessment, and proactive mitigation strategies. A comprehensive threat library classifies physical, third-party, external, and internal threats. ACA's iterative nature and feedback mechanisms enable continuous adaptation to emerging threats, ensuring sustained effectiveness. ACA allows healthcare providers to proactively identify and mitigate vulnerabilities, fostering trust and supporting the secure adoption of virtual care technologies., Comment: 6 pages, 3 figures, 3 tables
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- 2024
6. Russian roulette: Why you can have a deterministic potential-outcome framework, or an asymmetric utility function, but not both
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Gelman, Andrew and Mikhaeil, Jonas
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Statistics - Other Statistics - Abstract
It has been proposed in medical decision analysis to express the ``first do no harm'' principle as an asymmetric utility function in which the loss from killing a patient would count more than the gain from saving a life. Such a utility depends on unrealized potential outcomes, and we show how this yields a paradoxical decision recommendation in a simple hypothetical example involving games of Russian roulette. The problem is resolved if we allow the potential outcomes to be random variables. This leads us to conclude that, if you are interested in this sort of asymmetric utility function, you need to move to the stochastic potential outcome framework. We discuss the implications of the choice of parameterization in this setting., Comment: 7 pages
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- 2024
7. The prefrontal cortex, but not the medial temporal lobe, is associated with episodic memory in middle-aged persons with HIV
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Campbell, Laura M, Fennema-Notestine, Christine, Sundermann, Erin E, Barrett, Averi, Bondi, Mark W, Ellis, Ronald J, Franklin, Donald, Gelman, Benjamin, Gilbert, Paul E, Grant, Igor, Heaton, Robert K, Moore, David J, Morgello, Susan, Letendre, Scott, Patel, Payal B, Roesch, Scott, and Moore, Raeanne C
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Biological Psychology ,Psychology ,Aging ,Sexually Transmitted Infections ,Alzheimer's Disease ,Dementia ,Acquired Cognitive Impairment ,Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD) ,HIV/AIDS ,Behavioral and Social Science ,Biomedical Imaging ,Infectious Diseases ,Mental Health ,Basic Behavioral and Social Science ,Neurosciences ,Neurodegenerative ,Brain Disorders ,2.1 Biological and endogenous factors ,Mental health ,Neurological ,cognition ,Alzheimer's disease ,infectious disease ,HIV-associated neurocognitive disorders ,neuroimaging ,Prefrontal Cortex ,Temporal Lobe ,Humans ,HIV Infections ,Memory Disorders ,Magnetic Resonance Imaging ,Longitudinal Studies ,Neuropsychological Tests ,Aged ,Middle Aged ,Female ,Male ,Memory ,Episodic ,Cognitive Dysfunction ,Recognition ,Psychology ,Alzheimer’s disease ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Experimental Psychology ,Biomedical and clinical sciences ,Health sciences - Abstract
ObjectiveIdentifying persons with HIV (PWH) at increased risk for Alzheimer's disease (AD) is complicated because memory deficits are common in HIV-associated neurocognitive disorders (HAND) and a defining feature of amnestic mild cognitive impairment (aMCI; a precursor to AD). Recognition memory deficits may be useful in differentiating these etiologies. Therefore, neuroimaging correlates of different memory deficits (i.e., recall, recognition) and their longitudinal trajectories in PWH were examined.DesignWe examined 92 PWH from the CHARTER Program, ages 45-68, without severe comorbid conditions, who received baseline structural MRI and baseline and longitudinal neuropsychological testing. Linear and logistic regression examined neuroanatomical correlates (i.e., cortical thickness and volumes of regions associated with HAND and/or AD) of memory performance at baseline and multilevel modeling examined neuroanatomical correlates of memory decline (average follow-up = 6.5 years).ResultsAt baseline, thinner pars opercularis cortex was associated with impaired recognition (p = 0.012; p = 0.060 after correcting for multiple comparisons). Worse delayed recall was associated with thinner pars opercularis (p = 0.001) and thinner rostral middle frontal cortex (p = 0.006) cross sectionally even after correcting for multiple comparisons. Delayed recall and recognition were not associated with medial temporal lobe (MTL), basal ganglia, or other prefrontal structures. Recognition impairment was variable over time, and there was little decline in delayed recall. Baseline MTL and prefrontal structures were not associated with delayed recall.ConclusionsEpisodic memory was associated with prefrontal structures, and MTL and prefrontal structures did not predict memory decline. There was relative stability in memory over time. Findings suggest that episodic memory is more related to frontal structures, rather than encroaching AD pathology, in middle-aged PWH. Additional research should clarify if recognition is useful clinically to differentiate aMCI and HAND.
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- 2024
8. Therapeutic modulation of arginase with nor-NOHA alters immune responses in experimental mouse models of pulmonary tuberculosis including in the setting of Human Immunodeficiency Virus (HIV) co-infection
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Chauhan, Sadhana, Nusbaum, Rebecca J, Huante, Matthew B, Holloway, Alex J, Endsley, Mark A, Gelman, Benjamin B, Lisinicchia, Joshua G, and Endsley, Janice J
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- 2024
9. Developing Concepts of Authenticity: Insights from Parents' and Children's Conversations about Historical Significance
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Shaylene E. Nancekivell, Sarah Stilwell, and Susan A. Gelman
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Abstract The present study investigated children's understanding that an object's history may increase its significance, an appreciation that underpins the concept of "historical authenticity" (i.e., the idea that an item's history determines its true identity, beyond its functional or material qualities, leading people to value real items over copies or fakes). We examined the development of historical significance through the lens of parent-child conversations, and children's performance on an authenticity assessment. The final sample was American, 79.2% monoracial White, and mid-high socio-economic status (SES) and included 48 parent-child pairs: 24 with younger children (R = 3.5 to 4.5 years) and 24 with older children (R = 5.5 to 6.5 years). Parent-child pairs discussed three books we created, with three storylines: a museum (culturally authentic) storyline, a clean-up (personally authentic) storyline, and a control storyline. Across measures, conversations suggested that authenticity may begin as a "placeholder concept" that is initially rooted in a broad appreciation for the significance of old objects and only later filled in with specifics. This placeholder initially directs children's learning about authenticity by linking, in an unspecified way, the value and significance of objects to their past. For example, we found that young children appropriately appealed to history (vs. perceptual or functional features of objects) in contexts regarding authentic objects but struggled in determining which objects were more significant on the post-test assessment, suggesting that they attend to object history but are not yet sure how histories matter for making authenticity judgments. We also found some evidence that directing children's attention toward conceptual information related to object history may in turn direct them away from material or perceptual considerations, as seen in trade-offs in parents' and children's conversations. Together, this exploratory report offers many new avenues for work on the development of authenticity concepts in childhood.
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- 2024
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10. Children's Gender Essentialism and Prejudice: Testing Causal Links via an Experimental Manipulation
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E. B. Gross, Rachel D. Fine, Selin Gülgöz, Kristina R. Olson, and Susan A. Gelman
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Despite increases in visibility, gender-nonconforming young people continue to be at risk for bullying and discrimination. Prior work has established that gender essentialism in children correlates with prejudice against people who do not conform to gender norms, but to date no causal link has been established. The present study investigated this link more directly by testing whether children's gender essentialism and prejudice against gender nonconformity can be reduced by exposure to anti-essentialist messaging. Children ages 6--10 years of age (N = 102) in the experimental condition viewed a short video describing similarities between boys and girls and variation within each gender; children in the control condition (N = 102) viewed a corresponding video describing similarities between two types of climate and variation within each. Children then received measures of gender essentialism and prejudice against gender nonconformity. Finally, to ask whether manipulating children's gender essentialism extends to another domain, we included assessments of racial essentialism and prejudice. We found positive correlations between gender essentialism and prejudice against gender nonconformity; both also correlated negatively with participant age. However, we observed no differences between children in the experimental versus control conditions in overall essentialism or prejudice, indicating that our video was largely ineffective in manipulating essentialism. Accordingly, we were unable to provide evidence of a causal relationship between essentialism and prejudice. We did, however, see a difference between conditions on the discreteness measure, which is most closely linked to the wording in the video. This finding suggests that specific aspects of essentialism in young children may be modifiable.
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- 2024
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11. A Survey of Methods for Mitigating Barren Plateaus for Parameterized Quantum Circuits
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Gelman, Michelle
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Quantum Physics ,Computer Science - Emerging Technologies - Abstract
Barren Plateaus are a formidable challenge for hybrid quantum-classical algorithms that lead to flat plateaus in the loss function landscape making it difficult to take advantage of the expressive power of parameterized quantum circuits with gradient-based methods. Like in classical neural network models, parameterized quantum circuits suffer the same vanishing gradient issue due to large parameter spaces with non-convex landscapes. In this review, we present an overview of the different genesis for barren plateaus, mathematical formalisms of common themes around barren plateaus, and dives into gradients. The central objective is to provide a conceptual perspective between classical and quantum interpretations of vanishing gradients as well as dive into techniques involving cost functions, entanglement, and initialization strategies to mitigate barren plateaus. Addressing barren plateaus paves the way towards feasibility of many classically intractable applications for quantum simulation, optimization, chemistry, and quantum machine learning., Comment: 18 pages
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- 2024
12. Learning from and Responding to Statistical Criticism
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Gelman, Andrew
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- 2021
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13. The State of the Art in Causal Inference: Some Changes Since 1972
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Gelman, Andrew
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- 2021
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14. “You Think We are in the Stone Age, but We Have Already Made Progress—Where are You?”: A Qualitative Study of Ultra-orthodox Women’s Telemedicine Service Usage in Israel
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Chudner, Irit, Drach-Zahavy, Anat, Madjar, Batya, Gelman, Leah, and Habib, Sonia
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- 2024
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15. Children’s Understanding of Digital Tracking and Digital Privacy
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Gelman, Susan A., Nancekivell, Shaylene E., Lee, Young-eun, Schaub, Florian, Christakis, Dimitri A., editor, and Hale, Lauren, editor
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- 2025
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16. Multilevel Regression and Poststratification Interface: Application to Track Community-level COVID-19 Viral Transmission
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Si, Yajuan, Tran, Toan, Gabry, Jonah, Morris, Mitzi, and Gelman, Andrew
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Statistics - Applications - Abstract
In the absence of comprehensive or random testing throughout the COVID-19 pandemic, we have developed a proxy method for synthetic random sampling to estimate the actual viral incidence in the community, based on viral RNA testing of asymptomatic patients who present for elective procedures within a hospital system. The approach collects routine testing data on SARS-CoV-2 exposure among outpatients and performs statistical adjustments of sample representation using multilevel regression and poststratification (MRP). MRP adjusts for selection bias and yields stable small area estimates. We have developed an open-source, user-friendly MRP interface for public implementation of the statistical workflow. We illustrate the MRP interface with an application to track community-level COVID-19 viral transmission in the state of Michigan.
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- 2024
17. Nonequilibrium entropy from density estimation
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Gelman, Samuel D. and Cohen, Guy
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Condensed Matter - Statistical Mechanics - Abstract
Entropy is a central concept in physics, but can be challenging to calculate even for systems that are easily simulated. This is exacerbated out of equilibrium, where generally little is known about the distribution characterizing simulated configurations. However, modern machine learning algorithms can estimate the probability density characterizing an ensemble of images, given nothing more than sample images assumed to be drawn from this distribution. We show that by mapping system configurations to images, such approaches can be adapted to the efficient estimation of the density, and therefore the entropy, from simulated or experimental data. We then use this idea to obtain entropic limit cycles in a kinetic Ising model driven by an oscillating magnetic field. Despite being a global probe, we demonstrate that this allows us to identify and characterize stochastic dynamics at parameters near the dynamical phase transition.
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- 2024
18. Hierarchical Bayesian Models to Mitigate Systematic Disparities in Prediction with Proxy Outcomes
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Mikhaeil, Jonas, Gelman, Andrew, and Greengard, Philip
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Statistics - Methodology ,Statistics - Applications - Abstract
Label bias occurs when the outcome of interest is not directly observable and instead, modeling is performed with proxy labels. When the difference between the true outcome and the proxy label is correlated with predictors, this can yield systematic disparities in predictions for different groups of interest. We propose Bayesian hierarchical measurement models to address these issues. When strong prior information about the measurement process is available, our approach improves accuracy and helps with algorithmic fairness. If prior knowledge is limited, our approach allows assessment of the sensitivity of predictions to the unknown specifications of the measurement process. This can help practitioners gauge if enough substantive information is available to guarantee the desired accuracy and avoid disparate predictions when using proxy outcomes. We demonstrate our approach through practical examples.
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- 2024
19. Gemini: A Family of Highly Capable Multimodal Models
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Gemini Team, Anil, Rohan, Borgeaud, Sebastian, Alayrac, Jean-Baptiste, Yu, Jiahui, Soricut, Radu, Schalkwyk, Johan, Dai, Andrew M., Hauth, Anja, Millican, Katie, Silver, David, Johnson, Melvin, Antonoglou, Ioannis, Schrittwieser, Julian, Glaese, Amelia, Chen, Jilin, Pitler, Emily, Lillicrap, Timothy, Lazaridou, Angeliki, Firat, Orhan, Molloy, James, Isard, Michael, Barham, Paul R., Hennigan, Tom, Lee, Benjamin, Viola, Fabio, Reynolds, Malcolm, Xu, Yuanzhong, Doherty, Ryan, Collins, Eli, Meyer, Clemens, Rutherford, Eliza, Moreira, Erica, Ayoub, Kareem, Goel, Megha, Krawczyk, Jack, Du, Cosmo, Chi, Ed, Cheng, Heng-Tze, Ni, Eric, Shah, Purvi, Kane, Patrick, Chan, Betty, Faruqui, Manaal, Severyn, Aliaksei, Lin, Hanzhao, Li, YaGuang, Cheng, Yong, Ittycheriah, Abe, Mahdieh, Mahdis, Chen, Mia, Sun, Pei, Tran, Dustin, Bagri, Sumit, Lakshminarayanan, Balaji, Liu, Jeremiah, Orban, Andras, Güra, Fabian, Zhou, Hao, Song, Xinying, Boffy, Aurelien, Ganapathy, Harish, Zheng, Steven, Choe, HyunJeong, Weisz, Ágoston, Zhu, Tao, Lu, Yifeng, Gopal, Siddharth, Kahn, Jarrod, Kula, Maciej, Pitman, Jeff, Shah, Rushin, Taropa, Emanuel, Merey, Majd Al, Baeuml, Martin, Chen, Zhifeng, Shafey, Laurent El, Zhang, Yujing, Sercinoglu, Olcan, Tucker, George, Piqueras, Enrique, Krikun, Maxim, Barr, Iain, Savinov, Nikolay, Danihelka, Ivo, Roelofs, Becca, White, Anaïs, Andreassen, Anders, von Glehn, Tamara, Yagati, Lakshman, Kazemi, Mehran, Gonzalez, Lucas, Khalman, Misha, Sygnowski, Jakub, Frechette, Alexandre, Smith, Charlotte, Culp, Laura, Proleev, Lev, Luan, Yi, Chen, Xi, Lottes, James, Schucher, Nathan, Lebron, Federico, Rrustemi, Alban, Clay, Natalie, Crone, Phil, Kocisky, Tomas, Zhao, Jeffrey, Perz, Bartek, Yu, Dian, Howard, Heidi, Bloniarz, Adam, Rae, Jack W., Lu, Han, Sifre, Laurent, Maggioni, Marcello, Alcober, Fred, Garrette, Dan, Barnes, Megan, Thakoor, Shantanu, Austin, Jacob, Barth-Maron, Gabriel, Wong, William, Joshi, Rishabh, Chaabouni, Rahma, Fatiha, Deeni, Ahuja, Arun, Tomar, Gaurav Singh, Senter, Evan, Chadwick, Martin, Kornakov, Ilya, Attaluri, Nithya, Iturrate, Iñaki, Liu, Ruibo, Li, Yunxuan, Cogan, Sarah, Chen, Jeremy, Jia, Chao, Gu, Chenjie, Zhang, Qiao, Grimstad, Jordan, Hartman, Ale Jakse, Garcia, Xavier, Pillai, Thanumalayan Sankaranarayana, Devlin, Jacob, Laskin, Michael, Casas, Diego de Las, Valter, Dasha, Tao, Connie, Blanco, Lorenzo, Badia, Adrià Puigdomènech, Reitter, David, Chen, Mianna, Brennan, Jenny, Rivera, Clara, Brin, Sergey, Iqbal, Shariq, Surita, Gabriela, Labanowski, Jane, Rao, Abhi, Winkler, Stephanie, Parisotto, Emilio, Gu, Yiming, Olszewska, Kate, Addanki, Ravi, Miech, Antoine, Louis, Annie, Teplyashin, Denis, Brown, Geoff, Catt, Elliot, Balaguer, Jan, Xiang, Jackie, Wang, Pidong, Ashwood, Zoe, Briukhov, Anton, Webson, Albert, Ganapathy, Sanjay, Sanghavi, Smit, Kannan, Ajay, Chang, Ming-Wei, Stjerngren, Axel, Djolonga, Josip, Sun, Yuting, Bapna, Ankur, Aitchison, Matthew, Pejman, Pedram, Michalewski, Henryk, Yu, Tianhe, Wang, Cindy, Love, Juliette, Ahn, Junwhan, Bloxwich, Dawn, Han, Kehang, Humphreys, Peter, Sellam, Thibault, Bradbury, James, Godbole, Varun, Samangooei, Sina, Damoc, Bogdan, Kaskasoli, Alex, Arnold, Sébastien M. R., Vasudevan, Vijay, Agrawal, Shubham, Riesa, Jason, Lepikhin, Dmitry, Tanburn, Richard, Srinivasan, Srivatsan, Lim, Hyeontaek, Hodkinson, Sarah, Shyam, Pranav, Ferret, Johan, Hand, Steven, Garg, Ankush, Paine, Tom Le, Li, Jian, Li, Yujia, Giang, Minh, Neitz, Alexander, Abbas, Zaheer, York, Sarah, Reid, Machel, Cole, Elizabeth, Chowdhery, Aakanksha, Das, Dipanjan, Rogozińska, Dominika, Nikolaev, Vitaliy, Sprechmann, Pablo, Nado, Zachary, Zilka, Lukas, Prost, Flavien, He, Luheng, Monteiro, Marianne, Mishra, Gaurav, Welty, Chris, Newlan, Josh, Jia, Dawei, Allamanis, Miltiadis, Hu, Clara Huiyi, de Liedekerke, Raoul, Gilmer, Justin, Saroufim, Carl, Rijhwani, Shruti, Hou, Shaobo, Shrivastava, Disha, Baddepudi, Anirudh, Goldin, Alex, Ozturel, Adnan, Cassirer, Albin, Xu, Yunhan, Sohn, Daniel, Sachan, Devendra, Amplayo, Reinald Kim, Swanson, Craig, Petrova, Dessie, Narayan, Shashi, Guez, Arthur, Brahma, Siddhartha, Landon, Jessica, Patel, Miteyan, Zhao, Ruizhe, Villela, Kevin, Wang, Luyu, Jia, Wenhao, Rahtz, Matthew, Giménez, Mai, Yeung, Legg, Keeling, James, Georgiev, Petko, Mincu, Diana, Wu, Boxi, Haykal, Salem, Saputro, Rachel, Vodrahalli, Kiran, Qin, James, Cankara, Zeynep, Sharma, Abhanshu, Fernando, Nick, Hawkins, Will, Neyshabur, Behnam, Kim, Solomon, Hutter, Adrian, Agrawal, Priyanka, Castro-Ros, Alex, Driessche, George van den, Wang, Tao, Yang, Fan, Chang, Shuo-yiin, Komarek, Paul, McIlroy, Ross, Lučić, Mario, Zhang, Guodong, Farhan, Wael, Sharman, Michael, Natsev, Paul, Michel, Paul, Bansal, Yamini, Qiao, Siyuan, Cao, Kris, Shakeri, Siamak, Butterfield, Christina, Chung, Justin, Rubenstein, Paul Kishan, Agrawal, Shivani, Mensch, Arthur, Soparkar, Kedar, Lenc, Karel, Chung, Timothy, Pope, Aedan, Maggiore, Loren, Kay, Jackie, Jhakra, Priya, Wang, Shibo, Maynez, Joshua, Phuong, Mary, Tobin, Taylor, Tacchetti, Andrea, Trebacz, Maja, Robinson, Kevin, Katariya, Yash, Riedel, Sebastian, Bailey, Paige, Xiao, Kefan, Ghelani, Nimesh, Aroyo, Lora, Slone, Ambrose, Houlsby, Neil, Xiong, Xuehan, Yang, Zhen, Gribovskaya, Elena, Adler, Jonas, Wirth, Mateo, Lee, Lisa, Li, Music, Kagohara, Thais, Pavagadhi, Jay, Bridgers, Sophie, Bortsova, Anna, Ghemawat, Sanjay, Ahmed, Zafarali, Liu, Tianqi, Powell, Richard, Bolina, Vijay, Iinuma, Mariko, Zablotskaia, Polina, Besley, James, Chung, Da-Woon, Dozat, Timothy, Comanescu, Ramona, Si, Xiance, Greer, Jeremy, Su, Guolong, Polacek, Martin, Kaufman, Raphaël Lopez, Tokumine, Simon, Hu, Hexiang, Buchatskaya, Elena, Miao, Yingjie, Elhawaty, Mohamed, Siddhant, Aditya, Tomasev, Nenad, Xing, Jinwei, Greer, Christina, Miller, Helen, Ashraf, Shereen, Roy, Aurko, Zhang, Zizhao, Ma, Ada, Filos, Angelos, Besta, Milos, Blevins, Rory, Klimenko, Ted, Yeh, Chih-Kuan, Changpinyo, Soravit, Mu, Jiaqi, Chang, Oscar, Pajarskas, Mantas, Muir, Carrie, Cohen, Vered, Lan, Charline Le, Haridasan, Krishna, Marathe, Amit, Hansen, Steven, Douglas, Sholto, Samuel, Rajkumar, Wang, Mingqiu, Austin, Sophia, Lan, Chang, Jiang, Jiepu, Chiu, Justin, Lorenzo, Jaime Alonso, Sjösund, Lars Lowe, Cevey, Sébastien, Gleicher, Zach, Avrahami, Thi, Boral, Anudhyan, Srinivasan, Hansa, Selo, Vittorio, May, Rhys, Aisopos, Konstantinos, Hussenot, Léonard, Soares, Livio Baldini, Baumli, Kate, Chang, Michael B., Recasens, Adrià, Caine, Ben, Pritzel, Alexander, Pavetic, Filip, Pardo, Fabio, Gergely, Anita, Frye, Justin, Ramasesh, Vinay, Horgan, Dan, Badola, Kartikeya, Kassner, Nora, Roy, Subhrajit, Dyer, Ethan, Campos, Víctor Campos, Tomala, Alex, Tang, Yunhao, Badawy, Dalia El, White, Elspeth, Mustafa, Basil, Lang, Oran, Jindal, Abhishek, Vikram, Sharad, Gong, Zhitao, Caelles, Sergi, Hemsley, Ross, Thornton, Gregory, Feng, Fangxiaoyu, Stokowiec, Wojciech, Zheng, Ce, Thacker, Phoebe, Ünlü, Çağlar, Zhang, Zhishuai, Saleh, Mohammad, Svensson, James, Bileschi, Max, Patil, Piyush, Anand, Ankesh, Ring, Roman, Tsihlas, Katerina, Vezer, Arpi, Selvi, Marco, Shevlane, Toby, Rodriguez, Mikel, Kwiatkowski, Tom, Daruki, Samira, Rong, Keran, Dafoe, Allan, FitzGerald, Nicholas, Gu-Lemberg, Keren, Khan, Mina, Hendricks, Lisa Anne, Pellat, Marie, Feinberg, Vladimir, Cobon-Kerr, James, Sainath, Tara, Rauh, Maribeth, Hashemi, Sayed Hadi, Ives, Richard, Hasson, Yana, Noland, Eric, Cao, Yuan, Byrd, Nathan, Hou, Le, Wang, Qingze, Sottiaux, Thibault, Paganini, Michela, Lespiau, Jean-Baptiste, Moufarek, Alexandre, Hassan, Samer, Shivakumar, Kaushik, van Amersfoort, Joost, Mandhane, Amol, Joshi, Pratik, Goyal, Anirudh, Tung, Matthew, Brock, Andrew, Sheahan, Hannah, Misra, Vedant, Li, Cheng, Rakićević, Nemanja, Dehghani, Mostafa, Liu, Fangyu, Mittal, Sid, Oh, Junhyuk, Noury, Seb, Sezener, Eren, Huot, Fantine, Lamm, Matthew, De Cao, Nicola, Chen, Charlie, Mudgal, Sidharth, Stella, Romina, Brooks, Kevin, Vasudevan, Gautam, Liu, Chenxi, Chain, Mainak, Melinkeri, Nivedita, Cohen, Aaron, Wang, Venus, Seymore, Kristie, Zubkov, Sergey, Goel, Rahul, Yue, Summer, Krishnakumaran, Sai, Albert, Brian, Hurley, Nate, Sano, Motoki, Mohananey, Anhad, Joughin, Jonah, Filonov, Egor, Kępa, Tomasz, Eldawy, Yomna, Lim, Jiawern, Rishi, Rahul, Badiezadegan, Shirin, Bos, Taylor, Chang, Jerry, Jain, Sanil, Padmanabhan, Sri Gayatri Sundara, Puttagunta, Subha, Krishna, Kalpesh, Baker, Leslie, Kalb, Norbert, Bedapudi, Vamsi, Kurzrok, Adam, Lei, Shuntong, Yu, Anthony, Litvin, Oren, Zhou, Xiang, Wu, Zhichun, Sobell, Sam, Siciliano, Andrea, Papir, Alan, Neale, Robby, Bragagnolo, Jonas, Toor, Tej, Chen, Tina, Anklin, Valentin, Wang, Feiran, Feng, Richie, Gholami, Milad, Ling, Kevin, Liu, Lijuan, Walter, Jules, Moghaddam, Hamid, Kishore, Arun, Adamek, Jakub, Mercado, Tyler, Mallinson, Jonathan, Wandekar, Siddhinita, Cagle, Stephen, Ofek, Eran, Garrido, Guillermo, Lombriser, Clemens, Mukha, Maksim, Sun, Botu, Mohammad, Hafeezul Rahman, Matak, Josip, Qian, Yadi, Peswani, Vikas, Janus, Pawel, Yuan, Quan, Schelin, Leif, David, Oana, Garg, Ankur, He, Yifan, Duzhyi, Oleksii, Älgmyr, Anton, Lottaz, Timothée, Li, Qi, Yadav, Vikas, Xu, Luyao, Chinien, Alex, Shivanna, Rakesh, Chuklin, Aleksandr, Li, Josie, Spadine, Carrie, Wolfe, Travis, Mohamed, Kareem, Das, Subhabrata, Dai, Zihang, He, Kyle, von Dincklage, Daniel, Upadhyay, Shyam, Maurya, Akanksha, Chi, Luyan, Krause, Sebastian, Salama, Khalid, Rabinovitch, Pam G, M, Pavan Kumar Reddy, Selvan, Aarush, Dektiarev, Mikhail, Ghiasi, Golnaz, Guven, Erdem, Gupta, Himanshu, Liu, Boyi, Sharma, Deepak, Shtacher, Idan Heimlich, Paul, Shachi, Akerlund, Oscar, Aubet, François-Xavier, Huang, Terry, Zhu, Chen, Zhu, Eric, Teixeira, Elico, Fritze, Matthew, Bertolini, Francesco, Marinescu, Liana-Eleonora, Bölle, Martin, Paulus, Dominik, Gupta, Khyatti, Latkar, Tejasi, Chang, Max, Sanders, Jason, Wilson, Roopa, Wu, Xuewei, Tan, Yi-Xuan, Thiet, Lam Nguyen, Doshi, Tulsee, Lall, Sid, Mishra, Swaroop, Chen, Wanming, Luong, Thang, Benjamin, Seth, Lee, Jasmine, Andrejczuk, Ewa, Rabiej, Dominik, Ranjan, Vipul, Styrc, Krzysztof, Yin, Pengcheng, Simon, Jon, Harriott, Malcolm Rose, Bansal, Mudit, Robsky, Alexei, Bacon, Geoff, Greene, David, Mirylenka, Daniil, Zhou, Chen, Sarvana, Obaid, Goyal, Abhimanyu, Andermatt, Samuel, Siegler, Patrick, Horn, Ben, Israel, Assaf, Pongetti, Francesco, Chen, Chih-Wei "Louis", Selvatici, Marco, Silva, Pedro, Wang, Kathie, Tolins, Jackson, Guu, Kelvin, Yogev, Roey, Cai, Xiaochen, Agostini, Alessandro, Shah, Maulik, Nguyen, Hung, Donnaile, Noah Ó, Pereira, Sébastien, Friso, Linda, Stambler, Adam, Kuang, Chenkai, Romanikhin, Yan, Geller, Mark, Yan, ZJ, Jang, Kane, Lee, Cheng-Chun, Fica, Wojciech, Malmi, Eric, Tan, Qijun, Banica, Dan, Balle, Daniel, Pham, Ryan, Huang, Yanping, Avram, Diana, Shi, Hongzhi, Singh, Jasjot, Hidey, Chris, Ahuja, Niharika, Saxena, Pranab, Dooley, Dan, Potharaju, Srividya Pranavi, O'Neill, Eileen, Gokulchandran, Anand, Foley, Ryan, Zhao, Kai, Dusenberry, Mike, Liu, Yuan, Mehta, Pulkit, Kotikalapudi, Ragha, Safranek-Shrader, Chalence, Goodman, Andrew, Kessinger, Joshua, Globen, Eran, Kolhar, Prateek, Gorgolewski, Chris, Ibrahim, Ali, Song, Yang, Eichenbaum, Ali, Brovelli, Thomas, Potluri, Sahitya, Lahoti, Preethi, Baetu, Cip, Ghorbani, Ali, Chen, Charles, Crawford, Andy, Pal, Shalini, Sridhar, Mukund, Gurita, Petru, Mujika, Asier, Petrovski, Igor, Cedoz, Pierre-Louis, Li, Chenmei, Chen, Shiyuan, Santo, Niccolò Dal, Goyal, Siddharth, Punjabi, Jitesh, Kappaganthu, Karthik, Kwak, Chester, LV, Pallavi, Velury, Sarmishta, Choudhury, Himadri, Hall, Jamie, Shah, Premal, Figueira, Ricardo, Thomas, Matt, Lu, Minjie, Zhou, Ting, Kumar, Chintu, Jurdi, Thomas, Chikkerur, Sharat, Ma, Yenai, Yu, Adams, Kwak, Soo, Ähdel, Victor, Rajayogam, Sujeevan, Choma, Travis, Liu, Fei, Barua, Aditya, Ji, Colin, Park, Ji Ho, Hellendoorn, Vincent, Bailey, Alex, Bilal, Taylan, Zhou, Huanjie, Khatir, Mehrdad, Sutton, Charles, Rzadkowski, Wojciech, Macintosh, Fiona, Shagin, Konstantin, Medina, Paul, Liang, Chen, Zhou, Jinjing, Shah, Pararth, Bi, Yingying, Dankovics, Attila, Banga, Shipra, Lehmann, Sabine, Bredesen, Marissa, Lin, Zifan, Hoffmann, John Eric, Lai, Jonathan, Chung, Raynald, Yang, Kai, Balani, Nihal, Bražinskas, Arthur, Sozanschi, Andrei, Hayes, Matthew, Alcalde, Héctor Fernández, Makarov, Peter, Chen, Will, Stella, Antonio, Snijders, Liselotte, Mandl, Michael, Kärrman, Ante, Nowak, Paweł, Wu, Xinyi, Dyck, Alex, Vaidyanathan, Krishnan, R, Raghavender, Mallet, Jessica, Rudominer, Mitch, Johnston, Eric, Mittal, Sushil, Udathu, Akhil, Christensen, Janara, Verma, Vishal, Irving, Zach, Santucci, Andreas, Elsayed, Gamaleldin, Davoodi, Elnaz, Georgiev, Marin, Tenney, Ian, Hua, Nan, Cideron, Geoffrey, Leurent, Edouard, Alnahlawi, Mahmoud, Georgescu, Ionut, Wei, Nan, Zheng, Ivy, Scandinaro, Dylan, Jiang, Heinrich, Snoek, Jasper, Sundararajan, Mukund, Wang, Xuezhi, Ontiveros, Zack, Karo, Itay, Cole, Jeremy, Rajashekhar, Vinu, Tumeh, Lara, Ben-David, Eyal, Jain, Rishub, Uesato, Jonathan, Datta, Romina, Bunyan, Oskar, Wu, Shimu, Zhang, John, Stanczyk, Piotr, Zhang, Ye, Steiner, David, Naskar, Subhajit, Azzam, Michael, Johnson, Matthew, Paszke, Adam, Chiu, Chung-Cheng, Elias, Jaume Sanchez, Mohiuddin, Afroz, Muhammad, Faizan, Miao, Jin, Lee, Andrew, Vieillard, Nino, Park, Jane, Zhang, Jiageng, Stanway, Jeff, Garmon, Drew, Karmarkar, Abhijit, Dong, Zhe, Lee, Jong, Kumar, Aviral, Zhou, Luowei, Evens, Jonathan, Isaac, William, Irving, Geoffrey, Loper, Edward, Fink, Michael, Arkatkar, Isha, Chen, Nanxin, Shafran, Izhak, Petrychenko, Ivan, Chen, Zhe, Jia, Johnson, Levskaya, Anselm, Zhu, Zhenkai, Grabowski, Peter, Mao, Yu, Magni, Alberto, Yao, Kaisheng, Snaider, Javier, Casagrande, Norman, Palmer, Evan, Suganthan, Paul, Castaño, Alfonso, Giannoumis, Irene, Kim, Wooyeol, Rybiński, Mikołaj, Sreevatsa, Ashwin, Prendki, Jennifer, Soergel, David, Goedeckemeyer, Adrian, Gierke, Willi, Jafari, Mohsen, Gaba, Meenu, Wiesner, Jeremy, Wright, Diana Gage, Wei, Yawen, Vashisht, Harsha, Kulizhskaya, Yana, Hoover, Jay, Le, Maigo, Li, Lu, Iwuanyanwu, Chimezie, Liu, Lu, Ramirez, Kevin, Khorlin, Andrey, Cui, Albert, LIN, Tian, Wu, Marcus, Aguilar, Ricardo, Pallo, Keith, Chakladar, Abhishek, Perng, Ginger, Abellan, Elena Allica, Zhang, Mingyang, Dasgupta, Ishita, Kushman, Nate, Penchev, Ivo, Repina, Alena, Wu, Xihui, van der Weide, Tom, Ponnapalli, Priya, Kaplan, Caroline, Simsa, Jiri, Li, Shuangfeng, Dousse, Olivier, Piper, Jeff, Ie, Nathan, Pasumarthi, Rama, Lintz, Nathan, Vijayakumar, Anitha, Andor, Daniel, Valenzuela, Pedro, Lui, Minnie, Paduraru, Cosmin, Peng, Daiyi, Lee, Katherine, Zhang, Shuyuan, Greene, Somer, Nguyen, Duc Dung, Kurylowicz, Paula, Hardin, Cassidy, Dixon, Lucas, Janzer, Lili, Choo, Kiam, Feng, Ziqiang, Zhang, Biao, Singhal, Achintya, Du, Dayou, McKinnon, Dan, Antropova, Natasha, Bolukbasi, Tolga, Keller, Orgad, Reid, David, Finchelstein, Daniel, Raad, Maria Abi, Crocker, Remi, Hawkins, Peter, Dadashi, Robert, Gaffney, Colin, Franko, Ken, Bulanova, Anna, Leblond, Rémi, Chung, Shirley, Askham, Harry, Cobo, Luis C., Xu, Kelvin, Fischer, Felix, Xu, Jun, Sorokin, Christina, Alberti, Chris, Lin, Chu-Cheng, Evans, Colin, Dimitriev, Alek, Forbes, Hannah, Banarse, Dylan, Tung, Zora, Omernick, Mark, Bishop, Colton, Sterneck, Rachel, Jain, Rohan, Xia, Jiawei, Amid, Ehsan, Piccinno, Francesco, Wang, Xingyu, Banzal, Praseem, Mankowitz, Daniel J., Polozov, Alex, Krakovna, Victoria, Brown, Sasha, Bateni, MohammadHossein, Duan, Dennis, Firoiu, Vlad, Thotakuri, Meghana, Natan, Tom, Geist, Matthieu, Girgin, Ser tan, Li, Hui, Ye, Jiayu, Roval, Ofir, Tojo, Reiko, Kwong, Michael, Lee-Thorp, James, Yew, Christopher, Sinopalnikov, Danila, Ramos, Sabela, Mellor, John, Sharma, Abhishek, Wu, Kathy, Miller, David, Sonnerat, Nicolas, Vnukov, Denis, Greig, Rory, Beattie, Jennifer, Caveness, Emily, Bai, Libin, Eisenschlos, Julian, Korchemniy, Alex, Tsai, Tomy, Jasarevic, Mimi, Kong, Weize, Dao, Phuong, Zheng, Zeyu, Liu, Frederick, Zhu, Rui, Teh, Tian Huey, Sanmiya, Jason, Gladchenko, Evgeny, Trdin, Nejc, Toyama, Daniel, Rosen, Evan, Tavakkol, Sasan, Xue, Linting, Elkind, Chen, Woodman, Oliver, Carpenter, John, Papamakarios, George, Kemp, Rupert, Kafle, Sushant, Grunina, Tanya, Sinha, Rishika, Talbert, Alice, Wu, Diane, Owusu-Afriyie, Denese, Thornton, Chloe, Pont-Tuset, Jordi, Narayana, Pradyumna, Li, Jing, Fatehi, Saaber, Wieting, John, Ajmeri, Omar, Uria, Benigno, Ko, Yeongil, Knight, Laura, Héliou, Amélie, Niu, Ning, Gu, Shane, Pang, Chenxi, Li, Yeqing, Levine, Nir, Stolovich, Ariel, Santamaria-Fernandez, Rebeca, Goenka, Sonam, Yustalim, Wenny, Strudel, Robin, Elqursh, Ali, Deck, Charlie, Lee, Hyo, Li, Zonglin, Levin, Kyle, Hoffmann, Raphael, Holtmann-Rice, Dan, Bachem, Olivier, Arora, Sho, Koh, Christy, Yeganeh, Soheil Hassas, Põder, Siim, Tariq, Mukarram, Sun, Yanhua, Ionita, Lucian, Seyedhosseini, Mojtaba, Tafti, Pouya, Liu, Zhiyu, Gulati, Anmol, Liu, Jasmine, Ye, Xinyu, Chrzaszcz, Bart, Wang, Lily, Sethi, Nikhil, Li, Tianrun, Brown, Ben, Singh, Shreya, Fan, Wei, Parisi, Aaron, Stanton, Joe, Koverkathu, Vinod, Choquette-Choo, Christopher A., Li, Yunjie, Lu, TJ, Shroff, Prakash, Varadarajan, Mani, Bahargam, Sanaz, Willoughby, Rob, Gaddy, David, Desjardins, Guillaume, Cornero, Marco, Robenek, Brona, Mittal, Bhavishya, Albrecht, Ben, Shenoy, Ashish, Moiseev, Fedor, Jacobsson, Henrik, Ghaffarkhah, Alireza, Rivière, Morgane, Walton, Alanna, Crepy, Clément, Parrish, Alicia, Zhou, Zongwei, Farabet, Clement, Radebaugh, Carey, Srinivasan, Praveen, van der Salm, Claudia, Fidjeland, Andreas, Scellato, Salvatore, Latorre-Chimoto, Eri, Klimczak-Plucińska, Hanna, Bridson, David, de Cesare, Dario, Hudson, Tom, Mendolicchio, Piermaria, Walker, Lexi, Morris, Alex, Mauger, Matthew, Guseynov, Alexey, Reid, Alison, Odoom, Seth, Loher, Lucia, Cotruta, Victor, Yenugula, Madhavi, Grewe, Dominik, Petrushkina, Anastasia, Duerig, Tom, Sanchez, Antonio, Yadlowsky, Steve, Shen, Amy, Globerson, Amir, Webb, Lynette, Dua, Sahil, Li, Dong, Bhupatiraju, Surya, Hurt, Dan, Qureshi, Haroon, Agarwal, Ananth, Shani, Tomer, Eyal, Matan, Khare, Anuj, Belle, Shreyas Rammohan, Wang, Lei, Tekur, Chetan, Kale, Mihir Sanjay, Wei, Jinliang, Sang, Ruoxin, Saeta, Brennan, Liechty, Tyler, Sun, Yi, Zhao, Yao, Lee, Stephan, Nayak, Pandu, Fritz, Doug, Vuyyuru, Manish Reddy, Aslanides, John, Vyas, Nidhi, Wicke, Martin, Ma, Xiao, Eltyshev, Evgenii, Martin, Nina, Cate, Hardie, Manyika, James, Amiri, Keyvan, Kim, Yelin, Xiong, Xi, Kang, Kai, Luisier, Florian, Tripuraneni, Nilesh, Madras, David, Guo, Mandy, Waters, Austin, Wang, Oliver, Ainslie, Joshua, Baldridge, Jason, Zhang, Han, Pruthi, Garima, Bauer, Jakob, Yang, Feng, Mansour, Riham, Gelman, Jason, Xu, Yang, Polovets, George, Liu, Ji, Cai, Honglong, Chen, Warren, Sheng, XiangHai, Xue, Emily, Ozair, Sherjil, Angermueller, Christof, Li, Xiaowei, Sinha, Anoop, Wang, Weiren, Wiesinger, Julia, Koukoumidis, Emmanouil, Tian, Yuan, Iyer, Anand, Gurumurthy, Madhu, Goldenson, Mark, Shah, Parashar, Blake, MK, Yu, Hongkun, Urbanowicz, Anthony, Palomaki, Jennimaria, Fernando, Chrisantha, Durden, Ken, Mehta, Harsh, Momchev, Nikola, Rahimtoroghi, Elahe, Georgaki, Maria, Raul, Amit, Ruder, Sebastian, Redshaw, Morgan, Lee, Jinhyuk, Zhou, Denny, Jalan, Komal, Li, Dinghua, Hechtman, Blake, Schuh, Parker, Nasr, Milad, Milan, Kieran, Mikulik, Vladimir, Franco, Juliana, Green, Tim, Nguyen, Nam, Kelley, Joe, Mahendru, Aroma, Hu, Andrea, Howland, Joshua, Vargas, Ben, Hui, Jeffrey, Bansal, Kshitij, Rao, Vikram, Ghiya, Rakesh, Wang, Emma, Ye, Ke, Sarr, Jean Michel, Preston, Melanie Moranski, Elish, Madeleine, Li, Steve, Kaku, Aakash, Gupta, Jigar, Pasupat, Ice, Juan, Da-Cheng, Someswar, Milan, M., Tejvi, Chen, Xinyun, Amini, Aida, Fabrikant, Alex, Chu, Eric, Dong, Xuanyi, Muthal, Amruta, Buthpitiya, Senaka, Jauhari, Sarthak, Khandelwal, Urvashi, Hitron, Ayal, Ren, Jie, Rinaldi, Larissa, Drath, Shahar, Dabush, Avigail, Jiang, Nan-Jiang, Godhia, Harshal, Sachs, Uli, Chen, Anthony, Fan, Yicheng, Taitelbaum, Hagai, Noga, Hila, Dai, Zhuyun, Wang, James, Hamer, Jenny, Ferng, Chun-Sung, Elkind, Chenel, Atias, Aviel, Lee, Paulina, Listík, Vít, Carlen, Mathias, van de Kerkhof, Jan, Pikus, Marcin, Zaher, Krunoslav, Müller, Paul, Zykova, Sasha, Stefanec, Richard, Gatsko, Vitaly, Hirnschall, Christoph, Sethi, Ashwin, Xu, Xingyu Federico, Ahuja, Chetan, Tsai, Beth, Stefanoiu, Anca, Feng, Bo, Dhandhania, Keshav, Katyal, Manish, Gupta, Akshay, Parulekar, Atharva, Pitta, Divya, Zhao, Jing, Bhatia, Vivaan, Bhavnani, Yashodha, Alhadlaq, Omar, Li, Xiaolin, Danenberg, Peter, Tu, Dennis, Pine, Alex, Filippova, Vera, Ghosh, Abhipso, Limonchik, Ben, Urala, Bhargava, Lanka, Chaitanya Krishna, Clive, Derik, Li, Edward, Wu, Hao, Hongtongsak, Kevin, Li, Ianna, Thakkar, Kalind, Omarov, Kuanysh, Majmundar, Kushal, Alverson, Michael, Kucharski, Michael, Patel, Mohak, Jain, Mudit, Zabelin, Maksim, Pelagatti, Paolo, Kohli, Rohan, Kumar, Saurabh, Kim, Joseph, Sankar, Swetha, Shah, Vineet, Ramachandruni, Lakshmi, Zeng, Xiangkai, Bariach, Ben, Weidinger, Laura, Vu, Tu, Andreev, Alek, He, Antoine, Hui, Kevin, Kashem, Sheleem, Subramanya, Amar, Hsiao, Sissie, Hassabis, Demis, Kavukcuoglu, Koray, Sadovsky, Adam, Le, Quoc, Strohman, Trevor, Wu, Yonghui, Petrov, Slav, Dean, Jeffrey, and Vinyals, Oriol
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition - Abstract
This report introduces a new family of multimodal models, Gemini, that exhibit remarkable capabilities across image, audio, video, and text understanding. The Gemini family consists of Ultra, Pro, and Nano sizes, suitable for applications ranging from complex reasoning tasks to on-device memory-constrained use-cases. Evaluation on a broad range of benchmarks shows that our most-capable Gemini Ultra model advances the state of the art in 30 of 32 of these benchmarks - notably being the first model to achieve human-expert performance on the well-studied exam benchmark MMLU, and improving the state of the art in every one of the 20 multimodal benchmarks we examined. We believe that the new capabilities of the Gemini family in cross-modal reasoning and language understanding will enable a wide variety of use cases. We discuss our approach toward post-training and deploying Gemini models responsibly to users through services including Gemini, Gemini Advanced, Google AI Studio, and Cloud Vertex AI.
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- 2023
20. Model validation for aggregate inferences in out-of-sample prediction
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Kennedy, Lauren, Vehtari, Aki, and Gelman, Andrew
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Statistics - Methodology - Abstract
Generalization to new samples is a fundamental rationale for statistical modeling. For this purpose, model validation is particularly important, but recent work in survey inference has suggested that simple aggregation of individual prediction scores does not give a good measure of the score for population aggregate estimates. In this manuscript we explain why this occurs, propose two scoring metrics designed specifically for this problem, and demonstrate their use in three different ways. We show that these scoring metrics correctly order models when compared to the true score, although they do underestimate the magnitude of the score. We demonstrate with a problem in survey research, where multilevel regression and poststratification (MRP) has been used extensively to adjust convenience and low-response surveys to make population and subpopulation estimates.
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- 2023
21. The social aspects of illness: Children's and parents' explanations of the relation between social categories and illness in a predominantly white U.S. sample
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Menendez, David, Labotka, Danielle, Umscheid, Valerie A, and Gelman, Susan A
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Social and Personality Psychology ,Psychology ,Aging ,Basic Behavioral and Social Science ,Behavioral and Social Science ,Clinical Research ,Pediatric ,1.2 Psychological and socioeconomic processes ,Underpinning research ,Cognitive Sciences ,Developmental & Child Psychology ,Specialist studies in education ,Applied and developmental psychology - Abstract
The COVID-19 pandemic in the United States has had a disproportionate impact on Black, low-income, and elderly individuals. We recruited 175 predominantly white children ages 5-12 and their parents (N = 112) and asked which of two individuals (differing in age, gender, race, social class, or personality) was more likely to get sick with either COVID-19 or the common cold and why. Children and parents reported that older adults were more likely to get sick than younger adults, but reported few differences based on gender, race, social class, or personality. Children predominantly used behavioral explanations, but older children used more biological and structural explanations. Thus, children have some understanding of health disparities, and their understanding increases with age.
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- 2024
22. Characterization of a novel rabbit model of Peyronies disease.
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Gundogdu, Gokhan, Nguyen, Travis, Namasivayam, Aarthi, Starek, Stephanie, Gelman, Joel, and Mauney, Joshua
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Peyronies disease (PD) is a debilitating pathology which is associated with penile curvature and erectile dysfunction due to the formation of fibrotic plaques in the penile tunica albuginea. In the present study, we developed a novel rabbit model of PD via subtunical injection of recombinant transforming growth factor (TGF)-β1 protein and characterized erectile function and histopathological endpoints following plaque formation. Ten adult male, New Zealand white rabbits were randomized into 3 experimental groups including nonsurgical controls (NSC, N = 3) and those receiving subtunical injections of vehicle (N = 3) or TGF-β1 protein (0.5 µg/50 µl; N = 4). Following 1 month post-op, focal fibrous plaques composed of disorganized collagen type I and III bundles as well as fragmented elastin fibers at TGF-β1 injection sites were observed in contrast to control groups. Cavernosometric and cavernosographic evaluations revealed no significant differences in maximum intracorporal pressures or substantial curvature during papaverine-induced erection in either the vehicle or TGF-β1 cohorts. Immunohistochemical and histomorphometric analyses demonstrated significant increases in elastase 2B expression in TGF-β1-induced plaques as well as significant declines in matrix metalloproteinase (MMP)-2 and -9 expression relative to control levels. Our results demonstrate that PD-like fibrotic plaques can be created in the rabbit penile tunica albuginea following TGF-β1 injection.
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- 2024
23. A critical role for Macrophage-derived Cysteinyl-Leukotrienes in HIV-1 induced neuronal injury
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Yuan, Nina Y, Medders, Kathryn E, Sanchez, Ana B, Shah, Rohan, de Rozieres, Cyrus M, Ojeda-Juárez, Daniel, Maung, Ricky, Williams, Roy, Gelman, Benjamin B, Baaten, Bas J, Roberts, Amanda J, and Kaul, Marcus
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Medical Microbiology ,Biomedical and Clinical Sciences ,Immunology ,Acquired Cognitive Impairment ,HIV/AIDS ,Neurosciences ,Sexually Transmitted Infections ,Infectious Diseases ,Neurodegenerative ,Brain Disorders ,2.1 Biological and endogenous factors ,Mice ,Humans ,Animals ,HIV-1 ,Macrophages ,Leukotrienes ,Neurons ,p38 Mitogen-Activated Protein Kinases ,Mice ,Transgenic ,HIV Infections ,Cysteine ,HIV ,Neurotoxicity ,Cysteinyl leukotrienes ,Knockout ,HIVgp120-transgenic ,HIV associated neurocognitive disorder ,Behavior deficits ,P38 MAPK ,ERK1/2 signaling ,Psychology ,Neurology & Neurosurgery ,Biological psychology - Abstract
Macrophages (MΦ) infected with human immunodeficiency virus (HIV)-1 or activated by its envelope protein gp120 exert neurotoxicity. We found previously that signaling via p38 mitogen-activated protein kinase (p38 MAPK) is essential to the neurotoxicity of HIVgp120-stimulated MΦ. However, the associated downstream pathways remained elusive. Here we show that cysteinyl-leukotrienes (CysLT) released by HIV-infected or HIVgp120 stimulated MΦ downstream of p38 MAPK critically contribute to neurotoxicity. SiRNA-mediated or pharmacological inhibition of p38 MAPK deprives MΦ of CysLT synthase (LTC4S) and, pharmacological inhibition of the cysteinyl-leukotriene receptor 1 (CYSLTR1) protects cerebrocortical neurons against toxicity of both gp120-stimulated and HIV-infected MΦ. Components of the CysLT pathway are differentially regulated in brains of HIV-infected individuals and a transgenic mouse model of NeuroHIV (HIVgp120tg). Moreover, genetic ablation of LTC4S or CysLTR1 prevents neuronal damage and impairment of spatial memory in HIVgp120tg mice. Altogether, our findings suggest a novel critical role for cysteinyl-leukotrienes in HIV-associated brain injury.
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- 2024
24. Children’s biological causal models of disability
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Menendez, David and Gelman, Susan A
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Cognitive and Computational Psychology ,Psychology ,Genetics ,Aetiology ,2.1 Biological and endogenous factors ,Mental health ,Good Health and Well Being ,Disability ,Essentialism ,Illness ,Intuitive theories ,Biological reasoning ,Explanatory co -existence ,Artificial Intelligence and Image Processing ,Cognitive Sciences ,Developmental & Child Psychology ,Applied and developmental psychology ,Cognitive and computational psychology ,Social and personality psychology - Published
- 2024
25. Pseudomonas aeruginosa ventricular assist device infections: findings from ineffective phage therapies in five cases.
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Aslam, Saima, Roach, Dwayne, Nikolich, Mikeljon P, Biswas, Biswajit, Schooley, Robert T, Lilly-Bishop, Kimberley A, Rice, Gregory K, Cer, Regina Z, Hamilton, Theron, Henry, Matthew, Luong, Tiffany, Salabarria, Ann-Charlott, Sisk-Hackworth, Laura, Filippov, Andrey A, Lebreton, Francois, Hall, Lindsey, Nir-Paz, Ran, Onallah, Hadil, Livni, Gilat, Shostak, Eran, Wieder-Finesod, Anat, Yahav, Dafna, Yerushalmy, Ortal, Alkalay-Oren, Sivan, Braunstein, Ron, Khalifa, Leron, Rimon, Amit, Gelman, Daniel, and Hazan, Ronen
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Medical Microbiology ,Biomedical and Clinical Sciences ,Clinical Sciences ,Biodefense ,Assistive Technology ,Antimicrobial Resistance ,Infectious Diseases ,Prevention ,Cardiovascular ,Rare Diseases ,Heart Disease ,Vaccine Related ,Bioengineering ,Emerging Infectious Diseases ,Infection ,LVAD ,MDRO ,Pseudomonas aeruginosa ,device-related infection ,phage therapy ,Microbiology ,Pharmacology and Pharmaceutical Sciences ,Medical microbiology ,Pharmacology and pharmaceutical sciences - Abstract
Left ventricular assist devices (LVAD) are increasingly used for management of heart failure; infection remains a frequent complication. Phage therapy has been successful in a variety of antibiotic refractory infections and is of interest in treating LVAD infections. We performed a retrospective review of four patients that underwent five separate courses of intravenous (IV) phage therapy with concomitant antibiotic for treatment of endovascular Pseudomonas aeruginosa LVAD infection. We assessed phage susceptibility, bacterial strain sequencing, serum neutralization, biofilm activity, and shelf-life of phage preparations. Five treatments of one to four wild-type virulent phage(s) were administered for 14-51 days after informed consent and regulatory approval. There was no successful outcome. Breakthrough bacteremia occurred in four of five treatments. Two patients died from the underlying infection. We noted a variable decline in phage susceptibility following three of five treatments, four of four tested developed serum neutralization, and prophage presence was confirmed in isolates of two tested patients. Two phage preparations showed an initial titer drop. Phage biofilm activity was confirmed in two. Phage susceptibility alone was not predictive of clinical efficacy in P. aeruginosa endovascular LVAD infection. IV phage was associated with serum neutralization in most cases though lack of clinical effect may be multifactorial including presence of multiple bacterial isolates with varying phage susceptibility, presence of prophages, decline in phage titers, and possible lack of biofilm activity. Breakthrough bacteremia occurred frequently (while the organism remained susceptible to administered phage) and is an important safety consideration.
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- 2024
26. Longitudinal analysis of CSF HIV RNA in untreated people with HIV: Identification of CSF controllers
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Trunfio, Mattia, Tang, Bin, Okwuegbuna, Oluwakemi, Iudicello, Jennifer E, Bharti, Ajay, Moore, David J, Gelman, Benjamin B, Morgello, Susan, Patel, Payal B, Rubin, Leah H, Ances, Beau M, Gianella, Sara, Heaton, Robert K, Ellis, Ronald J, and Letendre, Scott L
- Subjects
Medical Microbiology ,Biomedical and Clinical Sciences ,Immunology ,HIV/AIDS ,Genetics ,Infectious Diseases ,Sexually Transmitted Infections ,Neurosciences ,2.1 Biological and endogenous factors ,Infection ,Good Health and Well Being ,Humans ,HIV-1 ,RNA ,Viral ,HIV Infections ,Iron ,Serum Globulins ,Viral Load ,antiretroviral naive ,blood-brain barrier ,central nervous system ,CSF control ,CSF ,plasma discordance ,HIV viral load ,CSF/plasma discordance ,antiretroviral naïve ,blood–brain barrier ,Microbiology ,Virology ,Clinical sciences ,Medical microbiology - Abstract
Interindividual variation of human immunodeficiency virus (HIV) RNA setpoint in cerebrospinal fluid (CSF) and its determinants are poorly understood, but relevant for HIV neuropathology, brain reservoirs, viral escape, and reseeding after antiretroviral interruptions. Longitudinal multicentric study on demographic, clinical, and laboratory correlates of CSF HIV RNA in 2000 follow-up visits from 597 people with HIV (PWH) off antiretroviral therapy (ART) and with plasma HIV RNA > the lower limit of quantification (LLQ). Factors associated with CSF control (CSFC; CSF HIV RNA LLQ) and with CSF/plasma discordance (CSF > plasma HIV RNA > LLQ) were also assessed through mixed-effects models. Posthoc and sensitivity analyses were performed for persistent CSFC and ART-naïve participants, respectively. Over a median follow-up of 2.1 years, CSF HIV RNA was associated with CD4+ and CD8+ T cells, CSF leukocytes, blood-brain barrier (BBB) integrity, biomarkers of iron and lipid metabolism, serum globulins, past exposure to lamivudine, and plasma HIV RNA (model p
- Published
- 2024
27. Ethical data acquisition for LLMs and AI algorithms in healthcare
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Williams, Marta, Karim, Wasie, Gelman, Justin, and Raza, Marium
- Published
- 2024
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28. Sex differences in the role of AKAP12 in behavioral function of middle-aged mice
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Ishikawa, Hidehiro, Kimura, Shintaro, Takase, Hajime, Borlongan, Maximillian, Fukuda, Norito, Hoshino, Tomonori, Hamanaka, Gen, Park, Ji Hyun, Shindo, Akihiro, Kim, Kyu-Won, Gelman, Irwin H., Lok, Josephine, Lo, Eng H., and Arai, Ken
- Published
- 2024
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29. Serotonin, cortisol, and DHEA-S levels in anxious and depressive pregnant women living with HIV
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Meza-Rodríguez, María del Pilar, Leff-Gelman, Philippe, Medina-Bastidas, Diana, Avila-García, Miroslava, Figueroa-Damián, Ricardo, and Camacho-Arroyo, Ignacio
- Published
- 2024
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30. Bacterial association with metals enables in vivo monitoring of urogenital microbiota using magnetic resonance imaging
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Donnelly, Sarah C., Varela-Mattatall, Gabriel E., Hassan, Salvan, Sun, Qin, Gelman, Neil, Thiessen, Jonathan D., Thompson, R. Terry, Prato, Frank S., Burton, Jeremy P., and Goldhawk, Donna E.
- Published
- 2024
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31. Correction: Standardized nomenclature for litigational legal prompting in generative language models
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Sivakumar, Aditya, Gelman, Ben, and Simmons, Robert
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- 2024
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32. Standardized nomenclature for litigational legal prompting in generative language models
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Sivakumar, Aditya, Gelman, Ben, and Simmons, Robert
- Published
- 2024
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33. The persuasive role of generic-you in online interactions
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Minxue Niu, Emily Mower Provost, David Jurgens, Susan A. Gelman, Ethan Kross, and Ariana Orvell
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Persuasion ,Generic-you ,Pronouns ,Medicine ,Science - Abstract
Abstract Persuasion plays a crucial role in human communication. Yet, convincing someone to change their mind is often challenging. Here, we demonstrate that a subtle linguistic device, generic-you (i.e., “you” that refers to people in general, e.g., “You win some, you lose some”), is associated with successfully shifting people’s pre-existing views in a naturalistic context. Leveraging Large Language Models, we conducted a preregistered study using a large ( $$N_{trials}$$ = 204,120) online debate dataset. Every use of generic-you in an argument was associated with an up to 14% percent increase in the odds of successful persuasion. These findings underscore the need to distinguish between the specific and generic uses of “you” in large-scale linguistic analyses, an aspect that has been overlooked in the literature. The robust association between generic-you and persuasion persisted with the inclusion of various covariates, and above and beyond other pronouns (i.e., specific-you, I or we). However, these findings do not imply causality. In Supplementary Experiment 2, arguments with generic-you (vs. first-person singular pronouns, e.g., I) were rated as more persuasive by open-minded individuals. In Supplementary Experiment 3, generic-you (vs. specific-you) arguments did not differentially predict attitude change. We discuss explanations for these results, including differential mechanisms, boundary conditions, and the possibility that people intuitively draw on generic-you when expressing more persuasive ideas. Together, these findings add to a growing literature on the interpersonal implications of broadening one’s perspective via a subtle shift in language, while motivating future research on contextual and individual differences that may moderate these effects.
- Published
- 2025
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34. Privacy Harm and Non-Compliance from a Legal Perspective
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Suvineetha Herath, Haywood Gelman, and Lisa Mckee
- Abstract
In today's data-sharing paradigm, personal data has become a valuable resource that intensifies the risk of unauthorized access and data breach. Increased data mining techniques used to analyze big data have posed significant risks to data security and privacy. Consequently, data breaches are a significant threat to individual privacy. Privacy is a multifaceted concept covering many areas, including the right to access, erasure, and rectify personal data. This paper explores the legal aspects of privacy harm and how they transform into legal action. Privacy harm is the negative impact to an individual as a result of the unauthorized release, gathering, distillation, or expropriation of personal information. Privacy Enhancing Technologies (PETs) emerged as a solution to address data privacy issues and minimize the risk of privacy harm. It is essential to implement privacy enhancement mechanisms to protect Personally Identifiable Information (PII) from unlawful use or access. FIPPs (Fair Information Practice Principles), based on the 1973 Code of Fair Information Practice (CFIP), and the Organization for Economic Cooperation and Development (OECD), are a collection of widely accepted, influential US codes that agencies use when evaluating information systems, processes, programs, and activities affecting individual privacy. Regulatory compliance places a responsibility on organizations to follow best practices to ensure the protection of individual data privacy rights. This paper will focus on FIPPs, relevance to US state privacy laws, their influence on OECD, and reference to the EU General Data Processing Regulation. (GDPR).
- Published
- 2023
35. For how many iterations should we run Markov chain Monte Carlo?
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Margossian, Charles C. and Gelman, Andrew
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Statistics - Computation - Abstract
Standard Markov chain Monte Carlo (MCMC) admits three fundamental control parameters: the number of chains, the length of the warmup phase, and the length of the sampling phase. These control parameters play a large role in determining the amount of computation we deploy. In practice, we need to walk a line between achieving sufficient precision and not wasting precious computational resources and time. We review general strategies to check the length of the warmup and sampling phases, and examine the three control parameters of MCMC in the contexts of CPU- and GPU-based hardware. Our discussion centers around three tasks: (1) inference about a latent variable, (2) computation of expectation values and quantiles, and (3) diagnostics to check the reliability of the estimators. This chapter begins with general recommendations on the control parameters of MCMC, which have been battle-tested over the years and often motivate defaults in Bayesian statistical software. Usually we do not know ahead of time how a sampler will interact with a target distribution, and so the choice of MCMC algorithm and its control parameters, tend to be based on experience, re-evaluated after simulations have been obtained and analyzed. The second part of this chapter provides a theoretical motivation for our recommended approach, with pointers to some concerns and open problems. We also examine recent developments on the algorithmic and hardware fronts, which motivate new computational approaches to MCMC.
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- 2023
36. Discovering the World of Viruses: Testing the Influence of Anthropomorphic Representations on Children’s Learning About COVID-19
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Menendez, David, Richardson, Emory, McNeil, Kalina M, and Gelman, Susan A
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Cognitive and Computational Psychology ,Psychology ,Coronaviruses ,Clinical Research ,Emerging Infectious Diseases ,Basic Behavioral and Social Science ,Pediatric ,Behavioral and Social Science ,Infectious Diseases ,Coronaviruses Disparities and At-Risk Populations ,anthropomorphism ,science education ,biological reasoning ,understanding of viruses ,conceptual development ,Specialist Studies in Education ,Cognitive Sciences ,Developmental & Child Psychology ,Specialist studies in education ,Applied and developmental psychology ,Cognitive and computational psychology - Published
- 2024
37. Application of the MENTOR model to advance One Health by promoting bat conservation and reducing zoonotic spillover risk
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Smith, Lindsay J, Gelman, Nancy, O’Mara, M Teague, Frick, Winifred F, Ronis, Emily M, Cameron, Kenneth N, Gonzales, Amanda, Coleman, Jeremy TH, Reichard, Jonathan D, and de Wit, Luz A
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Environmental Sciences ,Environmental Management ,Clinical Research ,Life on Land ,capacity development ,spillover ,nature-based solutions ,conservation leadership ,curriculum ,Architecture ,Environmental management ,Heritage ,archive and museum studies - Abstract
For few taxonomic groups do conservation efforts have such a disproportionate impact on biodiversity and human well-being as they do with bats. Bats face significant conservation challenges that affect their long-term viability, inhibit their ecosystem functions and services, and increase zoonotic spillover risks. Protecting bat populations and their habitats ultimately reduces these conservation threats, helps prevent pandemics, and supports essential ecosystem services. MENTOR-Bat is a fellowship program focused on strengthening technical research, and leadership capacity in the Global South to promote healthy environments where bats and humans can coexist with reduced risks of pathogen transmission. Co-designed by the United States Fish and Wildlife Service (USFWS) and Bat Conservation International (BCI), MENTOR-Bat mirrors the One Health framework by featuring a transdisciplinary team of three mentors and nine fellows from Cameroon, Colombia, and Indonesia. Fellows and mentors receive academic and field-based training on bat ecology and conservation, One Health, human dimensions of conservation, behavior change, strategic communications, international policy, adaptive management, project planning, conservation leadership, and public health. Fellows will then design and implement team pilot projects to advance One Health and bat conservation in their respective countries. Program evaluation of MENTOR-Bat is based on Kirkpatrick’s Hierarchy and focuses on measuring the development of established One Health core competences. By incorporating One Health and conservation within its activities, MENTOR-Bat can become a valuable programmatic template for transdisciplinary programming advancing evidence-based strategies for improving the well-being of bats, humans, and the environment.
- Published
- 2024
38. Development of male and female models of long urethral strictures in swine.
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Gundogdu, Gokhan, Nguyen, Travis, Eijansantos, Mando, Chaudhuri, Ambika, Barham, David, Gelman, Joel, and Mauney, Joshua
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Swine ,Tissue engineering ,Urethral stricture ,Wound healing - Abstract
BACKGROUND: Preclinical animal models which mimic the dimensions of long urethral strictures (>2 cm in length) encountered in the clinic are necessary to evaluate prospective graft designs for urethroplasty. The purpose of this study was to develop both male and female porcine models of long urethral strictures (∼4 cm in length) and characterize histological and functional outcomes of iatrogenic stricture formation between genders. METHODS: Focal, partial thickness urethral injuries were created over 5-6 cm long segments in male and female swine (N = 4 per gender) via electrocoagulation and the degree of stricture formation was monitored for up to 6 weeks by urethroscopy and retrograde urethrography. Animals were sacrificed following stricture confirmation and histological, immunohistochemical, and histomorphometric analyses were performed on strictured and uninjured control urethral segments to profile wound healing responses. RESULTS: Urethral stricture formation was detected in all female swine by 2 weeks and 100 % of male swine at 3.2 ± 1.8 weeks, post-operatively. The mean length of urethral strictures in both male and female swine was ∼4 cm. Substantial variations in the degree of stricture severity between sexes were observed with males exhibiting significant urethral stenosis and loss of α-smooth muscle actin+ smooth muscle bundles in comparison to controls, while females primarily displayed defects in pan-cytokeratin+ epithelia as well as functional urethral obstruction. CONCLUSIONS: Electrocoagulation injury is sufficient to produce long urethral strictures in male and female swine and the degree of stricture severity and nature of urethral obstruction was observed to be dependent on gender. Animal Protocol: AUP-19-150. KEY MESSAGE: Novel male and female models of long urethral strictures in swine were created to characterize histological and functional outcomes of iatrogenic stricture formation between genders.
- Published
- 2023
39. Artificial Intelligence and Aesthetic Judgment
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Hullman, Jessica, Holtzman, Ari, and Gelman, Andrew
- Subjects
Computer Science - Computers and Society ,Computer Science - Artificial Intelligence - Abstract
Generative AIs produce creative outputs in the style of human expression. We argue that encounters with the outputs of modern generative AI models are mediated by the same kinds of aesthetic judgments that organize our interactions with artwork. The interpretation procedure we use on art we find in museums is not an innate human faculty, but one developed over history by disciplines such as art history and art criticism to fulfill certain social functions. This gives us pause when considering our reactions to generative AI, how we should approach this new medium, and why generative AI seems to incite so much fear about the future. We naturally inherit a conundrum of causal inference from the history of art: a work can be read as a symptom of the cultural conditions that influenced its creation while simultaneously being framed as a timeless, seemingly acausal distillation of an eternal human condition. In this essay, we focus on an unresolved tension when we bring this dilemma to bear in the context of generative AI: are we looking for proof that generated media reflects something about the conditions that created it or some eternal human essence? Are current modes of interpretation sufficient for this task? Historically, new forms of art have changed how art is interpreted, with such influence used as evidence that a work of art has touched some essential human truth. As generative AI influences contemporary aesthetic judgment we outline some of the pitfalls and traps in attempting to scrutinize what AI generated media means., Comment: 16 pages, 4 figures
- Published
- 2023
40. In Pursuit of Campus-Wide Data Literacy: A Guide to Developing a Statistics Course for Students in Nonquantitative Fields
- Author
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Alexis Lerner and Andrew Gelman
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Course design ,Data literacy ,Data science ,Jewish studies ,Pedagogy ,Quantitative methods ,Probabilities. Mathematical statistics ,QA273-280 ,Special aspects of education ,LC8-6691 - Abstract
Data literacy for students in nonquantitative fields is important as statistics become the grammar of research and how the world’s decisions are made. Statistics courses are typically offered by mathematics or statistics departments or by social and natural sciences such as economics, political science, psychology, and biology. Here we discuss how to construct a statistics course for students in nonquantitative fields, with a goal of integrating statistical material with students’ substantive interests, using student-focused teaching methods and technology to increase student involvement. We demonstrate this kind of hybrid course with the example of an introductory applied statistics class, taught at both the University of Toronto’s Anne Tanenbaum Center for Jewish Studies and the United States Naval Academy.
- Published
- 2024
- Full Text
- View/download PDF
41. Unilateral hindlimb ischaemia‐induced systemic inflammation is associated with non‐ischaemic skeletal muscle inflammation
- Author
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William S. Evans, Gabriel S. Pena, Beata Gelman, Sarah Kuzmiak‐Glancy, and Steven J. Prior
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angiogenesis ,macrophage ,muscle atrophy ,neutrophil ,Physiology ,QP1-981 - Abstract
Abstract Skeletal muscle atrophy and dysfunction commonly accompany cardiovascular diseases such as peripheral arterial disease and may be partially attributable to systemic inflammation. We sought to determine whether acute systemic inflammation in a model of hindlimb ischaemia (HLI) could affect skeletal muscle macrophage infiltration, fibre size, or capillarization, independent of the ischaemia. Eight‐week‐old C57BL/6 male mice underwent either Sham or HLI surgery, and were killed 1, 3, or 7 days post‐surgery. Circulating inflammatory cytokine concentrations were measured, as well as immune cell infiltration and morphology of skeletal muscle from both limbs of HLI and Sham mice. In HLI compared with Sham mice at day 1, plasma interleukin‐1β levels were 216% higher (0.48 ± 0.10 vs. 0.15 ± 0.01 pg/μL, P = 0.005) and decreased by day 3. This was followed by increased macrophage presence in muscle from both ischaemic and non‐ischaemic limbs of HLI mice by day 7 (7.3‐ and 2.3‐fold greater than Sham, respectively, P
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- 2024
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42. Generic Language and Reporting Practices in Developmental Journals: Implications for Facilitating a More Representative Cognitive Developmental Science
- Author
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Jasmine M. DeJesus, Maureen A. Callanan, Valerie A. Umscheid, and Susan A. Gelman
- Abstract
As in other subfields of psychology, developmental science faces a long-standing problem of limited diversity in research participants. This issue especially raises concerns when researchers make unwarranted broad claims about their results, such as using generic language that implies that a finding is unvarying and applies across participants and contexts. Variation in editorial practices may contribute to the extent to which generic language is used or how much information is provided about participant demographics. The present study expands on an existing corpus of articles published in developmental psychology journals and examines the extent to which generic language differed by journal and sample characteristics (such as racial/ethnic diversity or sample size). We observed widespread use of generic language: 73% of articles included at least one generic statement in article components that were coded (i.e. titles, highlights, and abstracts). However, differences across journals were observed: Articles published in "Developmental Science" and "JECP" (which require authors to include short research highlights) tended to have higher rates of generic language than articles published in "Child Development" and "Developmental Psychology" (which did not require highlights). Articles that fully reported sample race and ethnicity also included fewer generic statements to describe their results than articles with more incomplete reporting. We conclude by highlighting the importance of editorial policies in shaping scholarship, as well as challenges and opportunities for researchers to consider when reporting demographic information in a global field and clearly and accurately communicating the importance of research findings.
- Published
- 2024
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43. Committing to Trauma-Informed Social Work Education in Chronic Syndemic Times
- Author
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Caroline Gelman, Anna Ortega-Williams, and Laura Katz
- Abstract
COVID-19 has revealed and intensified economic and health disparities, prompting a profound national and global examination of racist systems perpetuating such disadvantage. The historic confluence of COVID-19 with movements for social justice offers a window, which COVID fatigue may already be closing, for us to enact true change in the process and content of a graduate social work education. This moment calls for re-envisioned process and content that addresses issues of oppression, social justice, trauma, mental illness, and health. As social work educators with a specialization in trauma, we are thinking deeply about how to harness this juncture to shape a more rigorous and responsive social work educational process. We believe trauma-informed principles must be applied across the social work curriculum, beyond trauma-focused or clinical courses, and to our social work educational institutions. We offer examples of how we have revisioned social work training for ourselves and our students, from our multiple standpoints as faculty, administrator, and field advisor, for the complex challenges and opportunities of chronic syndemic times. We conclude with an invitation to shift away from the social work education status quo and truly practice what we teach.
- Published
- 2024
- Full Text
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44. An improved BISG for inferring race from surname and geolocation
- Author
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Greengard, Philip and Gelman, Andrew
- Subjects
Statistics - Applications ,Statistics - Methodology - Abstract
Bayesian Improved Surname Geocoding (BISG) is a ubiquitous tool for predicting race and ethnicity using an individual's geolocation and surname. Here we demonstrate that statistical dependence of surname and geolocation within racial/ethnic categories in the United States results in biases for minority subpopulations, and we introduce a raking-based improvement. Our method augments the data used by BISG--distributions of race by geolocation and race by surname--with the distribution of surname by geolocation obtained from state voter files. We validate our algorithm on state voter registration lists that contain self-identified race/ethnicity.
- Published
- 2023
45. Criticism as Asynchronous Collaboration: An Example from Social Science Research
- Author
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Gelman, Andrew
- Abstract
I discuss a published paper in political science that made a claim that aroused skepticism. The reanalysis is an example of how we, as consumers as well as producers of science, can engage with published work. This can be viewed as a sort of collaboration performed implicitly between the authors of a published paper and later researchers who want to understand or use the published work. [This paper was published in "Stat."]
- Published
- 2022
46. Stacking for Non-Mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors
- Author
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Yao, Yuling, Vehtari, Aki, and Gelman, Andrew
- Abstract
When working with multimodal Bayesian posterior distributions, Markov chain Monte Carlo (MCMC) algorithms have difficulty moving between modes, and default variational or mode-based approximate inferences will understate posterior uncertainty. And, even if the most important modes can be found, it is difficult to evaluate their relative weights in the posterior. Here we propose an approach using parallel runs of MCMC, variational, or mode-based inference to hit as many modes or separated regions as possible and then combine these using Bayesian stacking, a scalable method for constructing a weighted average of distributions. The result from stacking efficiently samples from multimodal posterior distribution, minimizes cross validation prediction error, and represents the posterior uncertainty better than variational inference, but it is not necessarily equivalent, even asymptotically, to fully Bayesian inference. We present theoretical consistency with an example where the stacked inference approximates the true data generating process from the misspecified model and a non-mixing sampler, from which the predictive performance is better than full Bayesian inference, hence the multimodality can be considered a blessing rather than a curse under model misspecification. We demonstrate practical implementation in several model families: latent Dirichlet allocation, Gaussian process regression, hierarchical regression, horseshoe variable selection, and neural networks.
- Published
- 2022
47. Causal quartets: Different ways to attain the same average treatment effect
- Author
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Gelman, Andrew, Hullman, Jessica, and Kennedy, Lauren
- Subjects
Statistics - Methodology ,Statistics - Applications - Abstract
The average causal effect can often be best understood in the context of its variation. We demonstrate with two sets of four graphs, all of which represent the same average effect but with much different patterns of heterogeneity. As with the famous correlation quartet of Anscombe (1973), these graphs dramatize the way in which real-world variation can be more complex than simple numerical summaries. The graphs also give insight into why the average effect is often much smaller than anticipated., Comment: 12 pages, 3 figures
- Published
- 2023
48. Community-developed checklists for publishing images and image analysis
- Author
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Schmied, Christopher, Nelson, Michael, Avilov, Sergiy, Bakker, Gert-Jan, Bertocchi, Cristina, Bischof, Johanna, Boehm, Ulrike, Brocher, Jan, Carvalho, Mariana, Chiritescu, Catalin, Christopher, Jana, Cimini, Beth, Conde-Sousa, Eduardo, Ebner, Michael, Ecker, Rupert, Eliceiri, Kevin, Fernandez-Rodriguez, Julia, Gaudreault, Nathalie, Gelman, Laurent, Grunwald, David, Gu, Tingting, Halidi, Nadia, Hammer, Mathias, Hartley, Matthew, Held, Marie, Jug, Florian, Kapoor, Varun, Koksoy, Ayse Aslihan, Lacoste, Judith, Dévédec, Sylvia Le, Guyader, Sylvie Le, Liu, Penghuan, Martins, Gabriel, Mathur, Aastha, Miura, Kota, Llopis, Paula Montero, Nitschke, Roland, North, Alison, Parslow, Adam, Payne-Dwyer, Alex, Plantard, Laure, Rizwan, Ali, Schroth-Diez, Britta, Schütz, Lucas, Scott, Ryan T., Seitz, Arne, Selchow, Olaf, Sharma, Ved, Spitaler, Martin, Srinivasan, Sathya, De Castillia, Caterina Strambio, Taatjes, Douglas, Tischer, Christian, and Jambor, Helena Klara
- Subjects
Quantitative Biology - Other Quantitative Biology - Abstract
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. However for scientists wishing to publish the obtained images and image analyses results, there are to date no unified guidelines. Consequently, microscopy images and image data in publications may be unclear or difficult to interpret. Here we present community-developed checklists for preparing light microscopy images and image analysis for publications. These checklists offer authors, readers, and publishers key recommendations for image formatting and annotation, color selection, data availability, and for reporting image analysis workflows. The goal of our guidelines is to increase the clarity and reproducibility of image figures and thereby heighten the quality of microscopy data is in publications., Comment: 28 pages, 8 Figures, 3 Supplmentary Figures, Manuscript, Essential recommendations for publication of microscopy image data
- Published
- 2023
- Full Text
- View/download PDF
49. That Escalated Quickly: An ML Framework for Alert Prioritization
- Author
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Gelman, Ben, Taoufiq, Salma, Vörös, Tamás, and Berlin, Konstantin
- Subjects
Computer Science - Cryptography and Security ,Computer Science - Machine Learning - Abstract
In place of in-house solutions, organizations are increasingly moving towards managed services for cyber defense. Security Operations Centers are specialized cybersecurity units responsible for the defense of an organization, but the large-scale centralization of threat detection is causing SOCs to endure an overwhelming amount of false positive alerts -- a phenomenon known as alert fatigue. Large collections of imprecise sensors, an inability to adapt to known false positives, evolution of the threat landscape, and inefficient use of analyst time all contribute to the alert fatigue problem. To combat these issues, we present That Escalated Quickly (TEQ), a machine learning framework that reduces alert fatigue with minimal changes to SOC workflows by predicting alert-level and incident-level actionability. On real-world data, the system is able to reduce the time it takes to respond to actionable incidents by $22.9\%$, suppress $54\%$ of false positives with a $95.1\%$ detection rate, and reduce the number of alerts an analyst needs to investigate within singular incidents by $14\%$., Comment: Submitted to Usenix Security Symposium
- Published
- 2023
50. Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach
- Author
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Guo, Han, Greengard, Philip, Wang, Hongyi, Gelman, Andrew, Kim, Yoon, and Xing, Eric P.
- Subjects
Computer Science - Machine Learning - Abstract
The canonical formulation of federated learning treats it as a distributed optimization problem where the model parameters are optimized against a global loss function that decomposes across client loss functions. A recent alternative formulation instead treats federated learning as a distributed inference problem, where the goal is to infer a global posterior from partitioned client data (Al-Shedivat et al., 2021). This paper extends the inference view and describes a variational inference formulation of federated learning where the goal is to find a global variational posterior that well-approximates the true posterior. This naturally motivates an expectation propagation approach to federated learning (FedEP), where approximations to the global posterior are iteratively refined through probabilistic message-passing between the central server and the clients. We conduct an extensive empirical study across various algorithmic considerations and describe practical strategies for scaling up expectation propagation to the modern federated setting. We apply FedEP on standard federated learning benchmarks and find that it outperforms strong baselines in terms of both convergence speed and accuracy.
- Published
- 2023
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