Search

Your search keyword '"Rousseau, Sylvain"' showing total 85 results
Start Over Author "Rousseau, Sylvain"
85 results on '"Rousseau, Sylvain"'

1. Harnessing Superclasses for Learning from Hierarchical Databases

Author

Urbani, Nicolas, Rousseau, Sylvain, Grandvalet, Yves, Tanzi, Leonardo, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Bifet, Albert, editor, Davis, Jesse, editor, Krilavičius, Tomas, editor, Kull, Meelis, editor, Ntoutsi, Eirini, editor, and Žliobaitė, Indrė, editor

Published
2024
Full Text
View/download PDF

2. CHARA/SPICA: a 6-telescope visible instrument for the CHARA Array

Author

Mourard, Denis, Berio, Philippe, Pannetier, Cyril, Nardetto, Nicolas, Allouche, Fatme, Bailet, Christophe, Dejonghe, Julien, Geneslay, Pierre, Jacqmart, Estelle, Lagarde, Stéphane, Lecron, Daniel, Morand, Frédéric, Rousseau, Sylvain, Salabert, David, Spang, Alain, Albrecht, Simon, Anugu, Narsireddy, Bourges, Laurent, Brummelaar, Theo A. ten, Creevey, Orlagh, Deheuvels, Sebastien, de Souza, Armando Domiciano, Gies, Doug, Ligi, Roxanne, Mella, Guillaume, Perraut, Karine, Schaefer, Gail, and Wittkowski, Markus

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

With a possible angular resolution down to 0.1-0.2 millisecond of arc using the 330 m baselines and the access to the 600-900 nm spectral domain, the CHARA Array is ideally configured for focusing on precise and accurate fundamental parameters of stars. CHARA/SPICA (Stellar Parameters and Images with a Cophased Array) aims at performing a large survey of stars all over the Hertzsprung-Russell diagram. This survey will also study the effects of the different kinds of variability and surface structure on the reliability of the extracted fundamental parameters. New surface-brightness-colour relations will be extracted from this survey, for general purposes on distance determination and the characterization of faint stars. SPICA is made of a visible 6T fibered instrument and of a near-infrared fringe sensor. In this paper, we detail the science program and the main characteristics of SPICA-VIS. We present finally the initial performance obtained during the commissioning.

Published
2022
Full Text
View/download PDF

3. SPICA-FT: The new fringe tracker of the CHARA array

Author

Pannetier, Cyril, Berio, Philippe, Mourard, Denis, Rousseau, Sylvain, Allouche, Fatme, Dejonghe, Julien, Bailet, Christophe, Lecron, Daniel, Cassaing, Frédéric, Bouquin, Jean-Baptiste Le, Perraut, Karine, Monnier, John D., Anugu, Narsireddy, and Brummelaar, Theo ten

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

SPICA-FT is part of the CHARA/SPICA instrument which combines a visible 6T fibered instrument (SPICAVIS) with a H-band 6T fringe sensor. SPICA-FT is a pairwise ABCD integrated optics combiner. The chip is installed in the MIRC-X instrument. The MIRC-X spectrograph could be fed either by the classical 6T fibered combiner or by the SPICA-FT integrated optics combiner. SPICA-FT also integrates a dedicated fringe tracking software, called the opd-controller communicating with the main delay line through a dedicated channel. We present the design of the integrated optics chip, its implementation in MIRC-X and the software architecture of the group-delay and phase-delay control loops. The final integrated optics chip and the software have been fully characterized in the laboratory. First on-sky tests of the integrated optics combiner began in 2020. We continue the on-sky tests of the whole system (combiner + software) in Spring and Summer 2022. We present the main results, and we deduce the preliminary performance of SPICA-FT.

Published
2022
Full Text
View/download PDF

4. Copula-based conformal prediction for Multi-Target Regression

Author

Messoudi, Soundouss, Destercke, Sébastien, and Rousseau, Sylvain

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Statistics - Machine Learning, 68T07
Abstract

There are relatively few works dealing with conformal prediction for multi-task learning issues, and this is particularly true for multi-target regression. This paper focuses on the problem of providing valid (i.e., frequency calibrated) multi-variate predictions. To do so, we propose to use copula functions applied to deep neural networks for inductive conformal prediction. We show that the proposed method ensures efficiency and validity for multi-target regression problems on various data sets., Comment: 17 pages, 8 figures, under review

Published
2021

5. HIRES, the high-resolution spectrograph for the ELT

Author

Marconi, Alessandro, Abreu, Manuel, Adibekyan, Vardan, Aliverti, Matteo, Prieto, Carlos Allende, Amado, Pedro J., Amate, Manuel, Artigau, Etienne, Augusto, Sergio R., Barros, Susana, Becerril, Santiago, Benneke, Bjorn, Bergin, Edwin, Berio, Philippe, Bezawada, Naidu, Boisse, Isabelle, Bonfils, Xavier, Bouchy, Francois, Broeg, Christopher, Cabral, Alexandre, Calvo-Ortega, Rocio, Martins, Bruno Leonardo Canto, Chazelas, Bruno, Chiavassa, Andrea, Christensen, Lise B., Cirami, Roberto, Coretti, Igor, Cristiani, Stefano, Parro, Vanderlei Cunha, Cupani, Guido, Leao, Izan de Castro, de Medeiros, Jose Renan, de Souza, Marco Antonio Furlan, Di Marcantonio, Paolo, Di Varano, Igor, D'Odorico, Valentina, Doyon, Rene, Drass, Holger, Figueira, Pedro, Fragoso, Ana Belen, Fynbo, Johan Peter Uldall, Gallo, Elena, Genoni, Matteo, Hernandez, Jonay I. Gonzalez, Haehnelt, Martin, Larrondo, Julie Hlavacek, Hughes, Ian, Huke, Philipp, Humphrey, Andrew, Kjeldsen, Hans, Korn, Andreas, Kouach, Driss, Landoni, Marco, Liske, Jochen, Lovis, Christophe, Lunney, David, Maiolino, Roberto, Malo, Lison, Marquart, Thomas, Martins, Carlos J. A. P., Mason, Elena, Monnier, John, Monteiro, Manuel A., Mordasini, Christoph, Morris, Tim, Murray, Graham J., Niedzielski, Andrzej, Nunes, Nelson, Oliva, Ernesto, Origlia, Livia, Palle, Enric, Pariani, Giorgio, Parr-Burman, Phil, Penate, Jose, Pepe, Francesco, Pinna, Enrico, Piskunov, Nikolai, Rasilla, Jose Luis, Rees, Phil, Rebolo, Rafael, Reiners, Ansgar, Riva, Marco, Rousseau, Sylvain, Sanna, Nicoletta, Santos, Nuno C., Sarajlic, Mirsad, Shen, Tzu-Chiang, Sortino, Francesca, Sosnowska, Danuta, Sousa, Sergio, Stempels, Eric, Strassmeier, Klaus G., Tenegi, Fabio, Tozzi, Andrea, Udry, Stephane, Valenziano, Luca, Vanzi, Leonardo, Weber, Michael, Woche, Manfred, Xompero, Marco, Zackrisson, Erik, and Osorio, Maria Rosa Zapatero

Subjects
Astrophysics - Instrumentation and Methods for Astrophysics
Abstract

HIRES will be the high-resolution spectrograph of the European Extremely Large Telescope at optical and near-infrared wavelengths. It consists of three fibre-fed spectrographs providing a wavelength coverage of 0.4-1.8 mic (goal 0.35-1.8 mic) at a spectral resolution of ~100,000. The fibre-feeding allows HIRES to have several, interchangeable observing modes including a SCAO module and a small diffraction-limited IFU in the NIR. Therefore, it will be able to operate both in seeing and diffraction-limited modes. ELT-HIRES has a wide range of science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Some of the top science cases will be the detection of bio signatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars (PopIII), tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The HIRES consortium is composed of more than 30 institutes from 14 countries, forming a team of more than 200 scientists and engineers., Comment: to appear in the ESO Messenger No.182, December 2020

Published
2020
Full Text
View/download PDF

6. Deep Conformal Prediction for Robust Models

Author

Messoudi, Soundouss, Rousseau, Sylvain, Destercke, Sébastien, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Kotenko, Igor, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Lesot, Marie-Jeanne, editor, Vieira, Susana, editor, Reformat, Marek Z., editor, Carvalho, João Paulo, editor, Wilbik, Anna, editor, Bouchon-Meunier, Bernadette, editor, and Yager, Ronald R., editor

Published
2020
Full Text
View/download PDF

7. Upgrading SPHERE with the second-stage adaptive optics system SAXO+: conceptual design of the opto-mechanical module

Author

Jackson, Kathryn J., Schmidt, Dirk, Vernet, Elise, Stadler, Eric, Schreiber, Laura, Cortecchia, Fausto, Lombini, Matteo, Diolaiti, Emiliano, Magnard, Yves, Rabou, Patrick, Rochat, Sylvain, De Rosa, Adriano, Malaguti, Giuseppe, Maurel, Didier, Morgante, Gianluca, Schiavone, Filomena, Terenzi, Luca, Chauvin, Gael, Ferreira, Florian, Gratton, Raffaele, Hubin, Norbert, Kasper, Markus, Langlois, Maud, Le Louarn, Miska, Loupias, Magali, Mazoyer, Johan, Milli, Julien, Mouillet, David, N’Diaye, Mamadou, Rousseau, Sylvain, Tallon, Michel, Vidal, Fabrice, Wildi, François, Zins, Gerard, and Boccaletti, Anthony

Published
2024
Full Text
View/download PDF

10. HARMONI at ELT: overview of the capabilities and expected performance of the ELT's first light, adaptive optics assisted integral field spectrograph.

Author

Thatte, Niranjan ., primary, Melotte, Dave, additional, Neichel, Benoit, additional, Le Mignant, David, additional, Bryson, Ian, additional, Clarke, Fraser, additional, Ferraro-Wood, Vanessa, additional, Fusco, Thierry, additional, Gonzalez, Oscar, additional, Schnetler, Hermine, additional, Tecza, Matthias, additional, Wilson, Sandi, additional, Álvarez Urueña, Alonso, additional, Vilaseca, Heribert A., additional, Arribas Mocoroa, Santiago, additional, Carracedo Carballale, Gonzalo José, additional, Crespo, Alejandro, additional, Estrada Piqueras, Alberto, additional, García García, Miriam, additional, Martínez Martín, Cecilia, additional, Pereira Santaella, Miguel, additional, Perna, Michele, additional, Piqueras López, Javier, additional, Bouché, Niolas, additional, Boudon, Didier, additional, Daguisé, Eric, additional, Disseau, Karen, additional, Fensch, Jérémy J., additional, Girardot, Adrien, additional, Guibert, Matthieu, additional, Jarno, Aurélien, additional, Jeanneau, Alexandre, additional, Krogager, Jens-Kristian, additional, Laurent, Florence, additional, Loupias, Magali, additional, Migniau, Jean-Emmanuel, additional, Piqueras, Laure, additional, Remillieux, Alban, additional, Richard, Johan, additional, Pecontal, Arlette, additional, Bardou, Lisa F., additional, Barr, David, additional, Cetre, Sylvain, additional, Deshmukh, Rishi, additional, Dimoudi, Sofia, additional, Dubbledam, Marc, additional, Dunn, Andrew, additional, Gadotti, Dimitra, additional, Guy, Joss J., additional, King, David L., additional, Little, David J., additional, McLeod, Anna, additional, Morris, Simon, additional, Morris, Tim, additional, O'Brien, Kieran S., additional, Ronson, Emily, additional, Smith, Russell, additional, Staykov, Lazar, additional, Swinbank, Mark, additional, Townson, Matthew, additional, Accardo, Matteo, additional, Alvarez Mendez, Domingo, additional, George, Elizabeth, additional, Hopgood, Joshua, additional, Ives, Derek, additional, Mehrgan, Leander, additional, Mueller, Eric, additional, Reyes-Moreno, Javier, additional, Conzelmann, Ralf, additional, Gutierrez Cheetham, Pablo, additional, Alonso-Sánchez, Ángel, additional, Battaglia, Giuseppina, additional, Cagigas Garcia, Miguel Angel, additional, Chulani, Haresh M., additional, Delgado García, Graciela C., additional, Fernández-Izquierdo, Patricia, additional, Fragoso López, Ana Belén, additional, García-Lorenzo, Begoña, additional, Hernández González, Alberto, additional, Hernández Suárez, Elvio, additional, Herreros Linares, Jose Miguel, additional, Joven, Enrique, additional, López López, Roberto, additional, Lujan Gonzalez, Alejandro Antonio, additional, Martín, Yolanda, additional, Mediavilla, Evencio, additional, Menéndez Mendoza, Saúl, additional, Montoya Martínez, Luz Maria, additional, Peñate Castro, José, additional, Pérez, Álvaro, additional, Rasilla, José Luis, additional, Rebolo-López, Rafael, additional, Rodríguez-Ramos, Luis Fernando, additional, Vega Moreno, Afrodisio, additional, Viera-Curbelo, Teodora, additional, Zanon Dametto, Natacha, additional, Carlotti, Alexis, additional, Correia, Jean-Jacques, additional, Curaba, Stéphane, additional, Delboulbé, Alain, additional, Guieu, Sylvain, additional, Hours, Adrien, additional, Hubert, Zoltan, additional, Jocou, Laurent, additional, Magnard, Yves, additional, Moulin, Thibaut, additional, Pancher, Fabrice, additional, Rabou, Patrick, additional, Stadler, Eric, additional, Vérove, Maxime, additional, Contini, Thierry, additional, Larrieu, Marie, additional, Boebion, Olivier, additional, Fantéï-Caujolle, Yan, additional, Lecron, Daniel, additional, Rousseau, Sylvain, additional, Amram, Philippe, additional, Beltramo-Martin, Olivier, additional, Bon, William, additional, Bonnefoi, Anne, additional, Ceria, William, additional, Challita, Zalpha, additional, Charles, Yannick, additional, Choquet, Elodie, additional, Correia, Carlos, additional, Costille, Anne, additional, Dohlen, Kjetil, additional, Ducret, Franck, additional, El Hadi, Kacem, additional, Gach, Jean-Luc, additional, Gimenez, Jean-Luc, additional, Groussin, Olivier, additional, Jaquet, Marc, additional, Jouve, Pierre, additional, Madec, Fabrice, additional, Pedreros Bustos, Felipe, additional, Renault, Edgard, additional, Sanchez, Patrice, additional, Vigan, Arthur, additional, Vola, Pascal, additional, Zavago, Annie, additional, Fétick, Romain, additional, Lim, Caroline, additional, Petit, Cyril, additional, Sauvage, Jean-Francois, additional, Védrenne, Nicolas, additional, Bagci, Fehim Taha, additional, Caldwell, Martin E., additional, Elliott, Ellis, additional, Hiscock, Peter, additional, Johnson, Emma, additional, Nalagatla, Murali, additional, Seitis, Aristea, additional, Wells, Mark, additional, Black, Martin, additional, Bond, Charlotte Z., additional, Brierley, Saskia, additional, Campbell, Kenneth, additional, Campbell, Neil, additional, Carruthers, James, additional, Cochrane, William, additional, Evans, Chris, additional, Harman, Joel, additional, Humphreys, William, additional, Louth, Thomas, additional, Miller, Chris, additional, Montgomery, David, additional, Murali, Meenu, additional, Murray, John, additional, O'Malley, Norman, additional, Sanchez-Janssen, Ruben, additional, Schwartz, Noah, additional, Smith, Patrick, additional, Strachan, Jonathan, additional, Todd, Stephen, additional, Watt, Stuart, additional, Wells, Martyn, additional, Yaqoob, Asim, additional, Bell, Eric, additional, Gnedin, Oleg O., additional, Gultekin, Kayhan, additional, Mateo, Mario, additional, Meyer, Michael, additional, Ahmad, Munadi, additional, Birkby, Jayne, additional, Booth, Michael, additional, Cappellari, Michele, additional, Castillo Dominguez, Edgar, additional, Chao Ortiz, Jorge, additional, Gooding, David, additional, Grisdale, Kearn, additional, Hidalgo Valadez, Andrea, additional, Hogan, Laurence, additional, Kariuki, James, additional, Lewis, Ian, additional, Lowe, Adam, additional, Ozer, Zeynep, additional, Routledge, Laurence, additional, Rigopoulou, Dimitra, additional, and York, Alec, additional

Published
2022
Full Text
View/download PDF

11. ANDES, the high resolution spectrograph for the ELT: science case, baseline design and path to construction

Author

Marconi, Alessandro, primary, Abreu, M., additional, Adibekyan, V., additional, Alberti, V., additional, Albrecht, S., additional, Alcaniz, J., additional, Aliverti, M., additional, Allende Prieto, C., additional, Alvarado Gómez, J. D., additional, Amado, P. J., additional, Amate, M., additional, Andersen, M. I., additional, Artigau, E., additional, Baker, C., additional, Baldini, V., additional, Balestra, A., additional, Barnes, S. A., additional, Baron, F., additional, Barros, S. C. C., additional, Bauer, S. M., additional, Beaulieu, M., additional, Bellido-Tirado, O., additional, Benneke, B., additional, Bensby, T., additional, Bergin, E. A., additional, Biazzo, K., additional, Bik, A., additional, Birkby, J., additional, Blind, N., additional, Boisse, I., additional, Bolmont, E., additional, Bonaglia, M., additional, Bonfils, X., additional, Borsa, F., additional, Brandeker, A., additional, Brandner, W., additional, Broeg, C. H., additional, Brogi, M., additional, Brousseau, D., additional, Brucalassi, A., additional, Brynnel, J., additional, Buchhave, L. A., additional, Buscher, D. F., additional, Cabral, A., additional, Calderone, G., additional, Calvo-Ortega, R., additional, Canto Martins, B. L., additional, Cantalloube, F., additional, Carbonaro, L., additional, Chauvin, G., additional, Chazelas, B., additional, Cheffot, A.-L., additional, Cheng, Y. S., additional, Chiavassa, A., additional, Christensen, L., additional, Cirami, R., additional, Cook, N. J., additional, Cooke, R. J., additional, Coretti, I., additional, Covino, S., additional, Cowan, N., additional, Cresci, G., additional, Cristiani, S., additional, Cunha Parro, V., additional, Cupani, G., additional, D'Odorico, V., additional, de Castro Leão, I., additional, De Cia, A., additional, De Medeiros, J. R., additional, Debras, F., additional, Debus, M., additional, Demangeon, O., additional, Dessauges-Zavadsky, M., additional, Di Marcantonio, P., additional, Dionies, F., additional, Doyon, R., additional, Dunn, J., additional, Ehrenreich, D., additional, Faria, J. P., additional, Feruglio, C., additional, Fisher, M., additional, Fontana, A., additional, Fumagalli, M., additional, Fusco, T., additional, Fynbo, J., additional, Gabella, O., additional, Gaessler, W., additional, Gallo, E., additional, Gao, X., additional, Genolet, L., additional, Genoni, M., additional, Giacobbe, P., additional, Giro, E., additional, Gonçalves, R. S., additional, Gonzalez, O., additional, González Hernández, J. I., additional, Gracia Témich, F., additional, Haehnelt, M. G., additional, Haniff, C., additional, Hatzes, A., additional, Helled, R., additional, Hoeijmakers, H.J., additional, Huke, P., additional, Järvinen, S., additional, Järvinen, A., additional, Kaminski, A., additional, Korn, A., additional, Kouach, D., additional, Kowzan, Grzegorz, additional, Kreidberg, L., additional, Landoni, M., additional, Lanotte, A., additional, Lavail, A., additional, Li, J., additional, Liske, J., additional, Lovis, C., additional, Lucatello, S., additional, Lunney, D., additional, MacIntosh, M., additional, Madhusudhan, N., additional, Magrini, L., additional, Maiolino, R., additional, Malo, L., additional, Man, A., additional, Marquart, T., additional, Marques, E. L., additional, Martins, A. M., additional, Martins, C. J. A. P., additional, Maslowski, P., additional, Mason, C., additional, Mason, E., additional, McCracken, R. A., additional, Mergo, P., additional, Micela, G., additional, Mitchell, T., additional, Mollière, P., additional, Monteiro, M., additional, Montgomery, D., additional, Mordasini, C., additional, Morin, J., additional, Mucciarelli, A., additional, Murphy, M. T., additional, N'Diaye, M., additional, Neichel, B., additional, Niedzielski, A. T., additional, Niemczura, E., additional, Nortmann, L., additional, Noterdaeme, P., additional, Nunes, N., additional, Oggioni, L., additional, Oliva, E., additional, Önel, H., additional, Origlia, L., additional, Östlin, G., additional, Palle, E., additional, Papaderos, P., additional, Pariani, G., additional, Peñate Castro, J., additional, Pepe, F., additional, Perreault Levasseur, L., additional, Petit, P., additional, Pino, L., additional, Piqueras, J., additional, Pollo, A., additional, Poppenhaeger, K., additional, Quirrenbach, A., additional, Rauscher, E., additional, Rebolo, R., additional, Redaelli, E. M. A., additional, Reffert, S., additional, Reid, D. T., additional, Reiners, A., additional, Richter, P., additional, Riva, M., additional, Rivoire, S., additional, Rodríguez-López, C., additional, Roederer, I. U., additional, Romano, D., additional, Rousseau, Sylvain, additional, Rowe, J., additional, Salvadori, S., additional, Santos, N., additional, Santos Diaz, P., additional, Sanz-Forcada, J., additional, Sarajlic, Mirsad, additional, Sauvage, J.-F., additional, Schäfer, S., additional, Schiavon, R. P., additional, Schmidt, T. M., additional, Selmi, C., additional, Sivanandam, S., additional, Sordet, M., additional, Sordo, R., additional, Sortino, F., additional, Sosnowska, D., additional, Sousa, S. G., additional, Stempels, E., additional, Strassmeier, K. G., additional, Suárez Mascareño, A., additional, Sulich, A., additional, Sun, X., additional, Tanvir, N.R., additional, Tenegi-Sanginés, F., additional, Thibault, S., additional, Thompson, S. J., additional, Tozzi, A., additional, Turbet, M., additional, Vallée, P., additional, Varas, R., additional, Venn, K., additional, Véran, J.-P., additional, Verma, A., additional, Viel, M., additional, Wade, G., additional, Waring, C., additional, Weber, M., additional, Weder, J., additional, Wehbe, B., additional, Weingrill, J., additional, Woche, M., additional, Xompero, M., additional, Zackrisson, E., additional, Zanutta, A., additional, Zapatero Osorio, M. R., additional, Zechmeister, M., additional, and Zimara, J., additional

Published
2022
Full Text
View/download PDF

12. CHARA/SPICA: a 6-telescope visible instrument for the CHARA Array

Author

Mourard, Denis, primary, Berio, Philippe, additional, Pannetier, Cyril, additional, Nardetto, Nicolas, additional, Allouche, Fatmé, additional, Bailet, Christophe, additional, Dejonghe, Julien, additional, Geneslay, Pierre, additional, Jacqmart, Estelle, additional, Lagarde, Stéphane, additional, Lecron, Daniel, additional, Morand, Frédéric, additional, Rousseau, Sylvain, additional, Salabert, David, additional, Spang, Alain, additional, Albrecht, Simon, additional, Anugu, Narsireddy, additional, Bourgès, Laurent, additional, ten Brummelaar, Theo A., additional, Creevey, Orlagh, additional, Deheuvels, Sebastien, additional, Domiciano, Armando, additional, Gies, Douglas R., additional, Ligi, Roxanne, additional, Mella, Guillaume, additional, Perraut, Karine, additional, Schaefer, Gail, additional, and Wittkowski, Markus, additional

Published
2022
Full Text
View/download PDF

13. SPICA-FT: the new fringe tracker of the CHARA array

Author

Pannetier, Cyril, primary, Bério, Philippe, additional, Mourard, Denis, additional, Rousseau, Sylvain, additional, Allouche, Fatmé, additional, Dejonghe, Julien, additional, Bailet, Christophe, additional, Lecron, Daniel, additional, Cassaing, Frédéric, additional, Le Bouquin, Jean-Baptiste, additional, Perraut, Karine, additional, Monnier, John D., additional, Anugu, Narsireddy, additional, and ten Brummelaar, Theo A., additional

Published
2022
Full Text
View/download PDF

14. Hierarchical Fringe Tracking, sky coverage and AGNs with the VLTI

Author

Petrov, Romain G., primary, Allouche, Fatmé, additional, Boskri, Abdelkarim, additional, Leftley, James H., additional, Hadjara, Massinissa, additional, Rousseau, Sylvain, additional, Lagarde, Stéphane, additional, Lopez, Bruno, additional, Millour, Florentin, additional, Chen, Xinyang, additional, Hao, Yinlei, additional, El Halkouj, Thami, additional, and Benkhaldoun, Zouhair, additional

Published
2022
Full Text
View/download PDF

16. ANDES, the high resolution spectrograph for the ELT:science case, baseline design and path to construction

Author

Marconi, Alessandro, Abreu, M., Adibekyan, V., Alberti, V., Albrecht, S., Alcaniz, J., Aliverti, M., Allende Prieto, C., Alvarado Gómez, J., Amado, P., Amate, M., Andersen, M., Artigau, E., Baker, C., Baldini, V., Balestra, A., Barnes, S., Baron, F., Barros, S., Bauer, S., Beaulieu, M., Bellido-Tirado, O., Benneke, B., Bensby, T., Bergin, E., Biazzo, K., Bik, A., Birkby, J., Blind, N., Boisse, I., Bolmont, E., Bonaglia, M., Bonfils, X., Borsa, F., Brandeker, A., Brandner, W., Broeg, C., Brogi, M., Brousseau, D., Brucalassi, A., Brynnel, J., Buchhave, L., Buscher, D., Cabral, A., Calderone, G., Calvo-Ortega, R., Canto Martins, B., Cantalloube, F., Carbonaro, L., Chauvin, G., Chazelas, B., Cheffot, A.-L., Cheng, Y., Chiavassa, A., Christensen, L., Cirami, R., Cook, N., Cooke, R., Coretti, I., Covino, S., Cowan, N., Cresci, G., Cristiani, S., Cunha Parro, V., Cupani, G., d'Odorico, V., de Castro Leão, I., de Cia, A., de Medeiros, J., Debras, F., Debus, M., Demangeon, O., Dessauges-Zavadsky, M., Di Marcantonio, P., Dionies, F., Doyon, R., Dunn, J., Ehrenreich, D., Faria, J., Feruglio, C., Fisher, M., Fontana, A., Fumagalli, M., Fusco, Thierry, Fynbo, J., Gabella, O., Gaessler, W., Gallo, E., Gao, X., Genolet, L., Genoni, M., Giacobbe, P., Giro, E., Gonçalves, R., Gonzalez, O., González Hernández, J., Gracia Témich, F., Haehnelt, M., Haniff, C., Hatzes, A., Helled, R., Hoeijmakers, H.J., Huke, P., Järvinen, S., Järvinen, A., Kaminski, A., Korn, A., Kouach, D., Kowzan, Grzegorz, Kreidberg, L., Landoni, M., Lanotte, A., Lavail, A., Li, J., Liske, J., Lovis, C., Lucatello, S., Lunney, D., Macintosh, M., Madhusudhan, N., Magrini, L., Maiolino, R., Malo, L., Man, A., Marquart, T., Marques, E., Martins, A., Martins, C., Maslowski, P., Mason, C., Mason, E., Mccracken, R., Mergo, P., Micela, G., Mitchell, T., Mollière, P., Monteiro, M., Montgomery, D., Mordasini, C., Morin, J., Mucciarelli, A., Murphy, M., N'Diaye, M., Neichel, B., Niedzielski, A., Niemczura, E., Nortmann, L., Noterdaeme, P., Nunes, N., Oggioni, L., Oliva, E., Önel, H., Origlia, L., Östlin, G., Palle, E., Papaderos, P., Pariani, G., Peñate Castro, J., Pepe, F., Perreault Levasseur, L., Petit, P., Pino, L., Piqueras, J., Pollo, A., Poppenhaeger, K., Quirrenbach, A., Rauscher, E., Rebolo, R., Redaelli, E., Reffert, S., Reid, D., Reiners, A., Richter, P., Riva, M., Rivoire, S., Rodríguez-López, C., Roederer, I., Romano, D., Rousseau, Sylvain, Rowe, J., Salvadori, S., Santos, N., Santos Diaz, P., Sanz-Forcada, J., Sarajlic, Mirsad, Sauvage, Jean-François, Schäfer, S., Schiavon, R., Schmidt, T., Selmi, C., Sivanandam, S., Sordet, M., Sordo, R., Sortino, F., Sosnowska, D., Sousa, S., Stempels, E., Strassmeier, K., Suárez Mascareño, A., Sulich, A., Sun, X., Tanvir, N.R., Tenegi-Sanginés, F., Thibault, S., Thompson, S., Tozzi, A., Turbet, M., Vallée, P., Varas, R., Venn, K., Véran, J.-P., Verma, A., Viel, M., Wade, G., Waring, C., Weber, M., Weder, J., Wehbe, B., Weingrill, J., Woche, M., Xompero, M., Zackrisson, E., Zanutta, A., Zapatero Osorio, M., Zechmeister, M., Zimara, J., Evans, Christopher J., Bryant, Julia J., Motohara, Kentaro, Institut de Planétologie et d'Astrophysique de Grenoble (IPAG), Centre National d'Études Spatiales [Toulouse] (CNES)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France -Institut national des sciences de l'Univers (INSU - CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Grenoble Alpes (UGA)-Météo-France, DOTA, ONERA, Université Paris Saclay [Palaiseau], ONERA-Université Paris-Saclay, Laboratoire Univers et Particules de Montpellier (LUPM), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Laboratoire d'Astrophysique de Marseille (LAM), Aix Marseille Université (AMU)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS), Institut d'Astrophysique de Paris (IAP), Institut national des sciences de l'Univers (INSU - CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), DOTA, ONERA [Salon], ONERA, Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Agenzia Spaziale Italiana, Fundação para a Ciência e a Tecnologia (Portugal), European Commission, Swedish Research Council, Australian Research Council, European Research Council, and National Science Foundation (US)

Subjects
[SDU.ASTR.CO]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], Diffraction limited IFU, fundamental physics, Extremely large telescope, fundamental physic, physics and evolution of galaxies, [PHYS.ASTR.SR]Physics [physics]/Astrophysics [astro-ph]/Solar and Stellar Astrophysics [astro-ph.SR], extremely large telescopes, [SDU.ASTR.IM]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Instrumentation and Methods for Astrophysic [astro-ph.IM], physics and evolution of stars, Fibre-fed spcetrograh, Sandage effect, exoplanets, High resolution spectroscopy, infrared spectrographs, stars and planets formation, Variation of physics fundamental constants, ground-based instruments, cosmology, Fundamental physics, Exoplanet atmospheres, Echelle spectrograph, high resolution spectrographs
Abstract

Ground-based and airborne instrumentation for astronomy IX (2022), Montreal, JUL 17-22, 2022.--Proceedings of SPIE - The International Society for Optical Engineering vol. 12184 Article number 1218424.-- Complete list of authors: Marconi, A.; Abreu, M.; Adibekyan, V.; Alberti, V.; Albrecht, S.; Alcaniz, J.; Aliverti, M.; Allende Prieto, C.; Gomez, J. D. Alvarado; Amado, P. J.; Amate, M.; Andersen, M. I.; Artigau, E.; Baker, C.; Baldini, V.; Balestra, A.; Barnes, S. A.; Baron, F.; Barros, S. C. C.; Bauer, S. M.; Beaulieu, M.; Bellido-Tirado, O.; Benneke, B.; Bensby, T.; Bergin, E. A.; Biazzo, K.; Bik, A.; Birkby, J. L.; Blind, N.; Boisse, I.; Bolmont, E.; Bonaglia, M.; Bonfils, X.; Borsa, F.; Brandeker, A.; Brandner, W.; Broeg, C. H.; Brogi, M.; Brousseau, D.; Brucalassi, A.; Brynnel, J.; Buchhave, L. A.; Buscher, D. F.; Cabral, A.; Calderone, G.; Calvo-Ortega, R.; Cantalloube, F.; Canto Martins, B. L.; Carbonaro, L.; Chauvin, G.; Chazelas, B.; Cheffot, A. -L.; Cheng, Y. S.; Chiavassa, A.; Christensen, L.; Cirami, R.; Cook, N. J.; Cooke, R. J.; Coretti, I.; Covino, S.; Cowan, N.; Cresci, G.; Cristiani, S.; Cunha Parro, V.; Cupani, G.; D'Odorico, V.; de Castro Leao, I.; De Cia, A.; De Medeiros, J. R.; Debras, F.; Debus, M.; Demangeon, O.; Dessauges-Zavadsky, M.; Di Marcantonio, P.; Dionies, F.; Doyon, R.; Dunn, J.; Ehrenreich, D.; Faria, J. P.; Feruglio, C.; Fisher, M.; Fontana, A.; Fumagalli, M.; Fusco, T.; Fynbo, J.; Gabella, O.; Gaessler, W.; Gallo, E.; Gao, X.; Genolet, L.; Genoni, M.; Giacobbe, P.; Giro, E.; Goncalves, R. S.; Gonzalez, O. A.; Gonzalez Hernandez, J. I.; Gracia Temich, F.; Haehnelt, M. G.; Haniff, C.; Hatzes, A.; Helled, R.; Hoeijmakers, H. J.; Huke, P.; Jaervinen, A. S.; Jaervinen, S. P.; Kaminski, A.; Korn, A. J.; Kouach, D.; Kowzan, G.; Kreidberg, L.; Landoni, M.; Lanotte, A.; Lavail, A.; Li, J.; Liske, J.; Lovis, C.; Lucatello, S.; Lunney, D.; MacIntosh, M. J.; Madhusudhan, N.; Magrini, L.; Maiolino, R.; Malo, L.; Man, A. W. S.; Marquart, T.; Marques, E. L.; Martins, C. J. A. P.; Martins, A. M.; Maslowski, P.; Mason, E.; Mason, C. A.; McCracken, R. A.; Mergo, P.; Micela, G.; Mitchell, T.; Molliere, P.; Monteiro, M. A.; Montgomery, D.; Mordasini, C.; Morin, J.; Mucciarelli, A.; Murphy, M. T.; N'Diaye, M.; Neichel, B.; Niedzielski, A. T.; Niemczura, E.; Nortmann, L.; Noterdaeme, P.; Nunes, N. J.; Oggioni, L.; Oliva, E.; Onel, H.; Origlia, L.; Ostlin, G.; Palle, E.; Papaderos, P.; Pariani, G.; Penate Castro, J.; Pepe, F.; Levasseur, L. Perreault; Petit, P.; Pino, L.; Piqueras, J.; Pollo, A.; Poppenhaeger, K.; Quirrenbach, A.; Rauscher, E.; Rebolo, R.; Redaelli, E. M. A.; Reffert, S.; Reid, D. T.; Reiners, A.; Richter, P.; Riva, M.; Rivoire, S.; Rodriguez-Lopez, C.; Roederer, I. U.; Romano, D.; Rousseau, S.; Rowe, J.; Salvadori, S.; Sanna, N.; Santos, N. C.; Diaz, P. Santos; Sanz-Forcada, J.; Sarajlic, M.; Sauvage, J. -F.; Schaefer, S.; Schiavon, R. P.; Schmidt, T. M.; Selmi, C.; Sivanandam, S.; Sordet, M.; Sordo, R.; Sortino, F.; Sosnowska, D.; Sousa, S. G.; Stempels, E.; Strassmeier, K. G.; Suarez Mascareno, A.; Sulich, A.; Sun, X.; Tanvir, N. R.; Tenegi-Sangines, F.; Thibault, S.; Thompson, S. J.; Tozzi, A.; Turbet, M.; Vallee, P.; Varas, R.; Venn, K. A.; Veran, J. -P.; Verma, A.; Viel, M.; Wade, G.; Waring, C.; Weber, M.; Weder, J.; Wehbe, B.; Weingrill, J.; Woche, M.; Xompero, M.; Zackrisson, E.; Zanutta, A.; Zapatero Osorio, M. R.; Zechmeister, M.; Zimara, J., The first generation of ELT instruments includes an optical-infrared high resolution spectrograph, indicated as ELT-HIRES and recently christened ANDES (ArmazoNes high Dispersion Echelle Spectrograph). ANDES consists of three fibre-fed spectrographs (UBV, RIZ, YJH) providing a spectral resolution of similar to 100,000 with a minimum simultaneous wavelength coverage of 0.4-1.8 mu m with the goal of extending it to 0.35-2.4 mu m with the addition of a K band spectrograph. It operates both in seeing- and diffraction-limited conditions and the fibre-feeding allows several, interchangeable observing modes including a single conjugated adaptive optics module and a small diffraction-limited integral field unit in the NIR. Its modularity will ensure that ANDES can be placed entirely on the ELT Nasmyth platform, if enough mass and volume is available, or partly in the Coude room. ANDES has a wide range of groundbreaking science cases spanning nearly all areas of research in astrophysics and even fundamental physics. Among the top science cases there are the detection of biosignatures from exoplanet atmospheres, finding the fingerprints of the first generation of stars, tests on the stability of Nature's fundamental couplings, and the direct detection of the cosmic acceleration. The ANDES project is carried forward by a large international consortium, composed of 35 Institutes from 13 countries, forming a team of more than 200 scientists and engineers which represent the majority of the scientific and technical expertise in the field among ESO member states., The Italian effort for ANDES is supported by the Italian National Institute for Astrophysics (INAF). The Portuguese participation is supported by FCT -Fundacao para a Ciencia e a Tecnologia through national funds and by FEDER through COMPETE2020 -Programa Operacional Competitividade e Internacionalizacao by these grants: UID/FIS/04434/2019, UIDB/04434/2020 & UIDP/04434/2020; POCI-01-0145-FEDER-032113 & PTDC/FIS-AST/32113/2017. Swedish participation in the ANDES project is made possible through the national Swedish ELT Instrumentation Consortium (SELTIC), suppored by the Swedish Research Council (VR). CJM acknowledges FCT and POCH/FSE (EC) support through Investigador FCT Contract 2021.01214.CEECIND/CP1658/CT0001. JLB acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program under grant agreement No 805445. MTM acknowledges the support of the Australian Research Council through Future Fellowship grant FT180100194 SS acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program under grant agreement No 804240. TMS acknowledgment the support from the SNF synergia grant CRSII5-193689 (BLUVES), With funding from the Spanish government through the Severo Ochoa Centre of Excellence accreditation SEV-2017-0709

Published
2022

22. Confiance de classe pour la prédiction de dette en gestion immobilière

Author

Messoudi, Soundouss, Destercke, Sébastien, Rousseau, Sylvain, Messoudi, Soundouss, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), and Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], prédiction conformelle mondrian, classification de dette, immobilier, prédiction conformelle inductive, ComputingMilieux_MISCELLANEOUS, confiance de classe, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

National audience

Published
2021

23. Compression collaborative de rayons de lumière pour le rendu distribué de Monte Carlo et applications

Author

Rousseau, Sylvain, Laboratoire Traitement et Communication de l'Information (LTCI), Institut Mines-Télécom [Paris] (IMT)-Télécom Paris, Institut Polytechnique de Paris, and Tamy Boubekeur

Subjects
Unit vectors, Vecteurs unitaires, Compression de données, Rendu de Monte Carlo, Informatique graphique, Image synthesis, Synthèse d'images, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Computer graphics, Monte Carlo rendering, Data compression, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

This thesis takes part in computer graphics. It studies one of its key elements, the unit vectors. We propose a new space of representation for sets of unit vectors and demonstrate its use on different kind of applications. To do so, we adapt the developed algorithms to each specific case.In the first part, we propose a compression algorithm for unorganized unit vectors sets. This method, called "Uniquant" generates coherency and uses it to change the space of representations of the data, in order to compresses collaboratively the vectors. We then use Uniquant in case of application to compress points cloud with orientations. The algorithm is able to compress the normals of the points on-the-fly.In the second part, we propose to compress a key element of the Monte Carlo rendering algorithm: the light ray. This data structure is used in most of the realistic light transport simulations. These simulations builds light paths, represented using 3D polylines that connect the virtual sensor (camera) to the light sources. The compression algorithm is used in the case of network distributed rendering, where a rendering engine that exploits numerous computers over a distant network is used to generate a single image. The hardware used by this kind of engine has become more and more popular over the last decade, especially with projects like SETI@Home, which enable access to a lot of computational power. This kind of hardware could easily be extended to take advantage of the machines in public institutions or in big companies that are typically used less than half of the time. This allows to increase the computational power without any need for new hardware. The method uses the fact that in the case of portal based distributed rendering engine, a lot of rays can be accumulated before being transferred on the network. The direction compression is extended to the ray's origins compression to study the impact of the compression loss of the rendering. We also show that compression can be correlated to the material properties.In the last part, we present QFib, an adaptation of Uniquant applicable to some medical data, which share some of the same mathematical constraints as light paths: brain tractograms in this case. They are often used in neurosciences to visualize the major neuronal influences. They enable neurosurgeons to predict possible effects of certain surgical procedures, and for the researchers to better understand the brain. The usage of this kind of data is difficult due to their large size, making them difficult to process, visualize, store, or even exchange.The introduced algorithm reduces their size by 10 in a few seconds on commonly used datasets. It ensures a loss that is way smaller than the MRI precision.; Cette thèse s'inscrit dans le domaine de l'informatique graphique en étudiant un élément clé, à savoir les vecteurs unitaires. Nous proposons un nouvel espace de représentation d'ensemble de vecteurs unitaires avant de montrer plusieurs applications adaptant celles-ci à différents types de données. Dans une première partie, nous proposons une méthode de compression d'ensembles de vecteurs unitaires désordonnées. Cette méthode, nommée UniQuant permet de réaliser une compression des données de manière collaborative, en générant de la cohérence puis en l'exploitant pour changer l'espace de représentation des données. Celle-ci est ensuite exploitée au travers d'une première application, permettant de compresser des ensembles de nuages de points munis de normales, et ainsi, permet de réaliser la compression des données à la volée. Nous proposons ensuite une application à un élément clé du rendu de Monte Carlo : le rayon de lumière. Celui-ci est la structure de donnée de base permettant de réaliser la simulation du transport de la lumière dans une scène virtuelle 3D en construisant des chemins de lumière, représentés à l’aide de polylignes 3D, reliant le capteur virtuel (caméra) aux différentes sources de lumière. L'application de la compression est utilisée dans le cas distribué, où un moteur construit pour exploiter un ensemble de machines sur des réseaux distants est utilisé. Les architectures matérielles de ce type sont devenues de plus en plus populaires avec l’apparition de projets tels que SETI@Home. Elles pourraient facilement être étendues pour exploiter les machines présentes dans les institutions publiques ou dans les entreprises et utilisées moins de la moitié du temps. Cela permettrait ainsi d’exploiter la puissance de calcul perdue. La technique proposée utilise la multitude de rayons disponibles dans le cas d’un moteur distribué exploitant des portails de lumière pour réaliser une compression collaborative, permettant d’accélérer les vitesses de transfert de données sur un réseau non local. La compression des directions est étendue à celle des origines pour examiner l'impact de la baisse de précision sur les rendus. Nous montrons également que la précision de la compression des directions peut être corrélée aux matériaux rencontrés. Enfin, nous présentons QFib, une adaptation d’UniQuant à d’autres types de données présentant le même type de contraintes mathématiques que les ensembles de rayons : des tractogrammes. Ceux-ci sont couramment utilisés en neurosciences pour visualiser les zones d’influence neuronales dans le cerveau. Ils permettent aux neurochirurgiens de prédire les effets possibles d’une opération, et aux chercheurs de mieux comprendre le fonctionnement du cerveau. L’utilisation de ce type de données est complexe du fait de leur taille, les rendant difficiles à visionner, traiter, stocker ou même échanger. L’algorithme introduit permet de diviser cette taille par 10 en quelques secondes pour des jeux de données typiquement utilisé, tout en assurant une perte inférieure à la précision des IRM ayant permis d'obtenir les jeux de données.

Published
2020

24. Conformal multi-target regression using neural networks

Author

Messoudi, Soundouss, Destercke, Sébastien, Rousseau, Sylvain, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Fondation Universitaire UTC, and Destercke, Sébastien

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], [INFO]Computer Science [cs], [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], [INFO] Computer Science [cs], [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; Multi-task learning is a domain that is still not fully studied in the conformal prediction framework, and this is particularly true for multi-target regression. Our work uses inductive conformal prediction along with deep neural networks to handle multi-target regression by exploring multiple extensions of existing single-target non-conformity measures and proposing new ones. This paper presents our approaches to work with conformal prediction in the multiple regression setting, as well as the results of our conducted experiments.

Published
2020

25. Prédiction conformelle profonde pour des modèles robustes

Author

Messoudi, Soundouss, Rousseau, Sylvain, Destercke, Sébastien, Messoudi, Soundouss, Heuristique et Diagnostic des Systèmes Complexes [Compiègne] (Heudiasyc), Université de Technologie de Compiègne (UTC)-Centre National de la Recherche Scientifique (CNRS), Image, Modélisation, Analyse, GEométrie, Synthèse (IMAGES), Laboratoire Traitement et Communication de l'Information (LTCI), Institut Mines-Télécom [Paris] (IMT)-Télécom Paris-Institut Mines-Télécom [Paris] (IMT)-Télécom Paris, and Laboratoire d'Excellence 'Maîtrise des Systèmes de Systèmes Technologiques' (Labex MS2T)

Subjects
[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], [INFO]Computer Science [cs], [INFO] Computer Science [cs], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]
Abstract

International audience; Les réseaux profonds, comme d'autres modèles, peuvent associer une confiance élevée à des prédictions peu fiables. Rendre ces modèles robustes et fiables est donc essentiel, surtout pour les décisions critiques. Ce papier montre expérimentalement que la prédiction conformelle, et plus particulièrement l'ap-proche de [Hechtlinger et al. (2018)], apporte une solution convaincante à ce défi. La prédiction conformelle fournit un ensemble de classes couvrant la vraie classe avec avec une fréquence choisie au préalable par l'utilisateur. Dans le cas où l'exemple à prédire est atypique, la prédiction conformelle prédira l'en-semble vide. Les expériences menées montrent le bon comportement de l'ap-proche conformelle, en particulier lorsque les données sont bruitées.

Published
2020

26. Collaborative light ray compression for distributed Monte Carlo rendering and applications

Author

Rousseau, Sylvain, STAR, ABES, Laboratoire Traitement et Communication de l'Information (LTCI), Institut Mines-Télécom [Paris] (IMT)-Télécom Paris, Institut Polytechnique de Paris, and Tamy Boubekeur

Subjects
Unit vectors, Vecteurs unitaires, Compression de données, Rendu de Monte Carlo, Informatique graphique, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, Image synthesis, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], Synthèse d'images, Computer graphics, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], Monte Carlo rendering, [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], Data compression, [INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC]
Abstract

This thesis takes part in computer graphics. It studies one of its key elements, the unit vectors. We propose a new space of representation for sets of unit vectors and demonstrate its use on different kind of applications. To do so, we adapt the developed algorithms to each specific case.In the first part, we propose a compression algorithm for unorganized unit vectors sets. This method, called "Uniquant" generates coherency and uses it to change the space of representations of the data, in order to compresses collaboratively the vectors. We then use Uniquant in case of application to compress points cloud with orientations. The algorithm is able to compress the normals of the points on-the-fly.In the second part, we propose to compress a key element of the Monte Carlo rendering algorithm: the light ray. This data structure is used in most of the realistic light transport simulations. These simulations builds light paths, represented using 3D polylines that connect the virtual sensor (camera) to the light sources. The compression algorithm is used in the case of network distributed rendering, where a rendering engine that exploits numerous computers over a distant network is used to generate a single image. The hardware used by this kind of engine has become more and more popular over the last decade, especially with projects like SETI@Home, which enable access to a lot of computational power. This kind of hardware could easily be extended to take advantage of the machines in public institutions or in big companies that are typically used less than half of the time. This allows to increase the computational power without any need for new hardware. The method uses the fact that in the case of portal based distributed rendering engine, a lot of rays can be accumulated before being transferred on the network. The direction compression is extended to the ray's origins compression to study the impact of the compression loss of the rendering. We also show that compression can be correlated to the material properties.In the last part, we present QFib, an adaptation of Uniquant applicable to some medical data, which share some of the same mathematical constraints as light paths: brain tractograms in this case. They are often used in neurosciences to visualize the major neuronal influences. They enable neurosurgeons to predict possible effects of certain surgical procedures, and for the researchers to better understand the brain. The usage of this kind of data is difficult due to their large size, making them difficult to process, visualize, store, or even exchange.The introduced algorithm reduces their size by 10 in a few seconds on commonly used datasets. It ensures a loss that is way smaller than the MRI precision., Cette thèse s'inscrit dans le domaine de l'informatique graphique en étudiant un élément clé, à savoir les vecteurs unitaires. Nous proposons un nouvel espace de représentation d'ensemble de vecteurs unitaires avant de montrer plusieurs applications adaptant celles-ci à différents types de données. Dans une première partie, nous proposons une méthode de compression d'ensembles de vecteurs unitaires désordonnées. Cette méthode, nommée UniQuant permet de réaliser une compression des données de manière collaborative, en générant de la cohérence puis en l'exploitant pour changer l'espace de représentation des données. Celle-ci est ensuite exploitée au travers d'une première application, permettant de compresser des ensembles de nuages de points munis de normales, et ainsi, permet de réaliser la compression des données à la volée. Nous proposons ensuite une application à un élément clé du rendu de Monte Carlo : le rayon de lumière. Celui-ci est la structure de donnée de base permettant de réaliser la simulation du transport de la lumière dans une scène virtuelle 3D en construisant des chemins de lumière, représentés à l’aide de polylignes 3D, reliant le capteur virtuel (caméra) aux différentes sources de lumière. L'application de la compression est utilisée dans le cas distribué, où un moteur construit pour exploiter un ensemble de machines sur des réseaux distants est utilisé. Les architectures matérielles de ce type sont devenues de plus en plus populaires avec l’apparition de projets tels que SETI@Home. Elles pourraient facilement être étendues pour exploiter les machines présentes dans les institutions publiques ou dans les entreprises et utilisées moins de la moitié du temps. Cela permettrait ainsi d’exploiter la puissance de calcul perdue. La technique proposée utilise la multitude de rayons disponibles dans le cas d’un moteur distribué exploitant des portails de lumière pour réaliser une compression collaborative, permettant d’accélérer les vitesses de transfert de données sur un réseau non local. La compression des directions est étendue à celle des origines pour examiner l'impact de la baisse de précision sur les rendus. Nous montrons également que la précision de la compression des directions peut être corrélée aux matériaux rencontrés. Enfin, nous présentons QFib, une adaptation d’UniQuant à d’autres types de données présentant le même type de contraintes mathématiques que les ensembles de rayons : des tractogrammes. Ceux-ci sont couramment utilisés en neurosciences pour visualiser les zones d’influence neuronales dans le cerveau. Ils permettent aux neurochirurgiens de prédire les effets possibles d’une opération, et aux chercheurs de mieux comprendre le fonctionnement du cerveau. L’utilisation de ce type de données est complexe du fait de leur taille, les rendant difficiles à visionner, traiter, stocker ou même échanger. L’algorithme introduit permet de diviser cette taille par 10 en quelques secondes pour des jeux de données typiquement utilisé, tout en assurant une perte inférieure à la précision des IRM ayant permis d'obtenir les jeux de données.

Published
2020

27. Progress of the CHARA/SPICA project

Author

Pannetier, Cyril, primary, Mourard, Denis, additional, Bério, Philippe, additional, Cassaing, Frédéric, additional, Allouche, Fatmé, additional, Anugu, Narsireddy, additional, Bailet, Christophe, additional, ten Brummelaar, Theo A., additional, Dejonghe, Julien, additional, Gies, Douglas R., additional, Jocou, Laurent, additional, Kraus, Stefan, additional, Lacour, Sylvestre, additional, Lagarde, Stéphane, additional, Le Bouquin, Jean-Baptiste, additional, Lecron, Daniel, additional, Monnier, John D., additional, Nardetto, Nicolas, additional, Patru, Fabien, additional, Rousselet-Perraut, Karine, additional, Petrov, Romain G., additional, Rousseau, Sylvain, additional, Stee, Philippe, additional, Sturmann, Judit, additional, and Sturmann, Laszlo, additional

Published
2020
Full Text
View/download PDF

28. HARMONI: first light spectroscopy for the ELT: instrument final design and quantitative performance predictions

Author

Thatte, Niranjan, primary, Bryson, Ian, additional, Clarke, Fraser, additional, Ferraro-Wood, Vanessa, additional, Fusco, Thierry, additional, Le Mignant, David, additional, Melotte, Dave J., additional, Neichel, Benoit, additional, Schnetler, Hermine, additional, Tecza, Matthias, additional, Arribas, Santiago, additional, Crespo, Alejandro, additional, Estrada Piqueras, Alberto, additional, García García, Miriam, additional, Pereira Santaella, Miguel, additional, Piqueras López, Javier, additional, Blaizot, Jeremy, additional, Bouché, Nicholas, additional, Boudon, Didier, additional, Chapuis, Diane, additional, Daguise, Eric, additional, Disseau, Karen, additional, Guibert, Mtthieu, additional, Jarno, Aurelien, additional, Jeanneau, Alexandre, additional, Laurent, Florence, additional, Loupias, Magali, additional, Migniau, Jean-Emmanuel, additional, Piqueras, Laure, additional, Remillieux, Alban, additional, Richard, Johan, additional, Pécontal-Rousset, Arlette, additional, Bardou, Lisa, additional, Close, Madeline M., additional, Deshmukh, Rishi, additional, Dimoudi, Sofia, additional, Dubbledam, Marc, additional, King, David, additional, Morris, Simon, additional, Morris, Timothy J., additional, O'Brien, Kieran S., additional, Staykov, Lazar, additional, Swinbank, Mark, additional, Townson, Matthew, additional, Younger, Eddy, additional, Accardo, Matteo, additional, Avarez Mendez, Domingo, additional, Conzelmann, Ralf, additional, Egner, Sebastian, additional, George, Elizabeth M., additional, Gonté, Frederic, additional, Hopgood, Joshua, additional, Ives, Derek, additional, Mehrgan, Leander, additional, Mueller, Eric, additional, Peroux, Celine, additional, Vernet, Joel, additional, Alonso-Sánchez, Ángel, additional, Giuseppina, Battaglia, additional, Cagigas, Miguel, additional, Delgado, Jose Miguel, additional, Fernandez Izquierdo, Patricia, additional, Fragoso López, Ana Belén, additional, García-Lorenzo, Maria Begoña, additional, Hernandez Suarez, Elvio, additional, Herreros Linares, José Miguel, additional, Joven, Enrique, additional, López, Roberto, additional, Martín Hernando, Yolanda, additional, Mediavilla, Evencio, additional, Monreal, Ana, additional, Peñate Castro, José, additional, Rasilla, Jose Luis, additional, Rebolo, Rafael, additional, Rodríguez-Ramos, Luis Fernando, additional, Vega Moreno, Afrodisio, additional, Viera, Teodora, additional, Carlotti, Alexis, additional, Correia, Jean-Jacques, additional, Delboulbe, Alain, additional, Guieu, Sylvain, additional, Hours, Adrien, additional, Hubert, Zoltan, additional, Jocou, Laurent, additional, Magnard, Yves, additional, Moulin, Thibaut, additional, Pancher, Fabrice, additional, Rabou, Patrick, additional, Stadler, Eric, additional, Contini, Thierry, additional, Larrieu, Marie, additional, Fantei-Caujolle, Yan, additional, Lecron, Daniel, additional, Rousseau, Sylvain, additional, Beltramo-Martin, Olivier, additional, Bon, William, additional, Bonnefoi, Anne, additional, Ceria, William, additional, Choquet, Elodie, additional, Correia, Carlos, additional, Costille, Anne, additional, Dohlen, Kjetil, additional, Ducret, Franck, additional, El Hadi, Kacem, additional, Epinat, Benoit, additional, Fetick, Romain, additional, Gach, Jean-Luc, additional, Groussin, Oliver, additional, Jaafar, Issa, additional, Le Merrer, Joel, additional, Llored, Marc, additional, Pedreros, Felipe, additional, Renault, Edgard, additional, Sanchez, Patrice, additional, Vigan, Arthur, additional, Vola, Pascal, additional, Lim, Caroline, additional, Vedrenne, Nicola, additional, Petit, Cyril, additional, Sauvage, Jean-Francois, additional, Bagci, Taha, additional, Cann, Nick, additional, Chao Ortiz, Jorge, additional, Elliott, Ellis, additional, Seitis, Tea, additional, Tosh, Ian, additional, Anderson, Josh, additional, Black, Martin, additional, Bond, Charlotte, additional, Born, Andy J., additional, Campbell, Kenny, additional, Campbell, Neil, additional, Carruthers, James, additional, Cochrane, William, additional, Dobson, Naomi, additional, Evans, Chris J., additional, Gallie, Angus, additional, Gonzalez, Oscar, additional, Harman, Joel, additional, Henry, David M., additional, Humphreys, William, additional, Louth, Tom, additional, Miller, Chris, additional, Montgomery, David M., additional, Murray, John, additional, O'Malley, Norman, additional, Ritchie, Lynn, additional, Sanchez-Janssen, Ruben, additional, Schwartz, Noah, additional, Smith, Patrick, additional, Watt, Stuart, additional, Wells, Martyn, additional, Wilson, Sandi, additional, Gultekin, Kayhan K., additional, Mateo, Mario L., additional, Meyer, Michael, additional, Valluri, Monica, additional, Ahmad, Munadi, additional, Booth, Michael, additional, Capone, John I., additional, Cappellari, Michele, additional, Gooding, David, additional, Grisdale, Kearn, additional, Hidalgo, Andrea, additional, Kariuki, James, additional, Lewis, Ian, additional, Lowe, Adam, additional, Lynn, Jim, additional, Menduina, Alvaro, additional, Ozer, Zeynep, additional, Preece, Roy, additional, Rigopoulou, Dimitra, additional, Rodrigues, Myriam, additional, and Routledge, Laurence, additional

Published
2020
Full Text
View/download PDF

31. Hierarchical Fringe Tracking, sky coverage and AGNs at the VLTI

Author

Mérand, Antoine, Sallum, Stephanie, Sanchez-Bermudez, Joel, Petrov, Romain G., Allouche, Fatmé, Boskri, Abdelkarim, Leftley, James, Hadjara, Massinissa, Rousseau, Sylvain, Lagarde, Stéphane, Lopez, Bruno, Millour, Florentin, Chen, Xinyang, Hao, Yinlei, Elhalkouj, Thami, and Benkhaldoun, Zouhair

Published
2022
Full Text
View/download PDF

32. QFib: Fast and Accurate Compression of White Matter Tractograms

Author

Rousseau, Sylvain, Mercier, Corentin, Gori, Pietro, Bloch, Isabelle, Boubekeur, Tamy, HAL, TelecomParis, Image, Modélisation, Analyse, GEométrie, Synthèse (IMAGES), Laboratoire Traitement et Communication de l'Information (LTCI), Institut Mines-Télécom [Paris] (IMT)-Télécom Paris-Institut Mines-Télécom [Paris] (IMT)-Télécom Paris, Département Images, Données, Signal (IDS), and Télécom ParisTech

Subjects
[INFO.INFO-IM]Computer Science [cs]/Medical Imaging, [INFO.INFO-IM] Computer Science [cs]/Medical Imaging, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

33. CHARA/SPICA: the new 6T visible combiner for the CHARA Array

Author

Kammerer, Jens, Sallum, Stephanie, Sanchez-Bermudez, Joel, Mourard, Denis, Meilland, Anthony, Ibañez Bustos, Romina, Jonak, Juraj, Berio, Philippe, Dejonghe, Julien, Lecron, Daniel, Morand, Frédéric, Salabert, David, Allouche, Fatmé, Anugu, Narsireddy, Bosio, Sandra, Bourges, Laurent, Creevey, Orlagh, Deheuvels, Sébastien, Domiciano de Souza, Armando, Ebrahimkutty, Nayeem, Gies, Doug R., Kubiak, Karolina, Ligi, Roxanne, Ligon, Robert, Mella, Guillaume, Nardetto, Nicolas, Perraut, Karine, Pitiot, Christophe, Rousseau, Sylvain, Vrard, Mathieu, Schaefer, Gail H., Spang, Alain, Turner, Nils, Wittkowski, Markus, and Zumbo, Florian

Published
2024
Full Text
View/download PDF

34. ELT-HIRES, the high resolution spectrograph for the ELT: results from the Phase A study

Author

Di Marcantonio, Paolo, Maiolino, Roberto, Oliva, Ernesto, Origlia, Livia, Riva, Marco, Valenziano, Luca, Allende Prieto, Carlos, Amado, Pedro, Amate, Manuel, Becerril, Santiago, Bezawada, Naidu, Boisse, Isabelle, Bouchy, François, Cabral, Alexandre, Chazelas, Bruno, Cirami, Roberto, Coretti, Igor, Cristiani, Stefano, Cupani, Guido, D'odorico, Valentina, De Souza, M. A. F., Marconi, Alessandro, De Castro Leão, Izan, De Medeiros, José, Di Varano, Igor, Drass, Holger, Figueira, Pedro, Fragoso Lopez, Ana Belen, Fynbo, Johan, Genoni, Matteo, González Hernández, Jonay, Hughes, Ian, Huke, Philipp, Kjeldsen, Hans, Korn, Andreas, Landoni, Marco, Liske, Jochen, Lovis, Christophe, Martins, Carlos, Mason, Elena, Monteiro, Manuel, Morris, Timothy J., Niedzielski, Andrzej, Pallé, Enric, Parr-burman, Phil, Pepe, Francesco, Piskunov, Nikolai, Rasilla, José Luis, Rebolo-lópez, Rafael, Rousseau, Sylvain, Sanna, Nicoletta, Santos, Nuno, Shen, Tzu-chiang, Sortino, Francesca, Sosnowska, Danuta, Sousa, Sergio, Stempels, Eric, Strassmeier, Klaus G., Tenegi, Fabio, Tozzi, Andrea, Udry, Stéphane, Vanzi, Leonardo, Weber, Michael, Woche, Manfred, Xompero, Marco, Zackrisson, Erik, Augusto, Sergio Ribeiro, Parro, Vanderlei Cunha, Murray, Graham, Rees, Phil, Haehnelt, Martin, Marquart, Thomas, Takami, Hideki, Evans, Christopher J., Simard, Luc, Di Marcantonio, Paolo, Maiolino, Roberto, Oliva, Ernesto, Origlia, Livia, Riva, Marco, Valenziano, Luca, Allende Prieto, Carlos, Amado, Pedro, Amate, Manuel, Becerril, Santiago, Bezawada, Naidu, Boisse, Isabelle, Bouchy, François, Cabral, Alexandre, Chazelas, Bruno, Cirami, Roberto, Coretti, Igor, Cristiani, Stefano, Cupani, Guido, D'odorico, Valentina, De Souza, M. A. F., Marconi, Alessandro, De Castro Leão, Izan, De Medeiros, José, Di Varano, Igor, Drass, Holger, Figueira, Pedro, Fragoso Lopez, Ana Belen, Fynbo, Johan, Genoni, Matteo, González Hernández, Jonay, Hughes, Ian, Huke, Philipp, Kjeldsen, Hans, Korn, Andreas, Landoni, Marco, Liske, Jochen, Lovis, Christophe, Martins, Carlos, Mason, Elena, Monteiro, Manuel, Morris, Timothy J., Niedzielski, Andrzej, Pallé, Enric, Parr-burman, Phil, Pepe, Francesco, Piskunov, Nikolai, Rasilla, José Luis, Rebolo-lópez, Rafael, Rousseau, Sylvain, Sanna, Nicoletta, Santos, Nuno, Shen, Tzu-chiang, Sortino, Francesca, Sosnowska, Danuta, Sousa, Sergio, Stempels, Eric, Strassmeier, Klaus G., Tenegi, Fabio, Tozzi, Andrea, Udry, Stéphane, Vanzi, Leonardo, Weber, Michael, Woche, Manfred, Xompero, Marco, Zackrisson, Erik, Augusto, Sergio Ribeiro, Parro, Vanderlei Cunha, Murray, Graham, Rees, Phil, Haehnelt, Martin, Marquart, Thomas, Takami, Hideki, Evans, Christopher J., and Simard, Luc

Published
2018

36. MATISSE: Performance in laboratory, results of AIV in Paranal, and first results on sky

Author

Lagarde, Stéphane, primary, Robbe-Dubois, Sylvie, primary, Allouche, Fatmé, primary, Berio, Philippe, primary, Lopez, Bruno, primary, Petrov, Romain, primary, Millour, Florentin, primary, Matter, Alexis, primary, Cruzalèbes, Pierre, primary, Antonelli, Pierre, primary, Bailet, Christophe, primary, Bresson, Yves, primary, Clausse, Jean-Michel, primary, Fantei-Caujolle, Yan, primary, Marcotto, Aurélie, primary, Meilland, Anthony, primary, Morel, Sebastien, primary, Rousseau, Sylvain, primary, Soulain, Anthony, primary, Zins, Gérard, primary, Laun, Werner, primary, Adler, Tobias, primary, Klein, Ralf, primary, Maurer, Tobias, primary, Eldswick, Eddy, primary, Heininger, Matthias, primary, Bristow, Paul, primary, Glindemann, Andreas, primary, Hubin, Norbert, primary, Jochum, Liselotte, primary, Rivinus, Thomas, primary, Schoeller, Markus, primary, Beltran, Juan, primary, Bourget, Pierre, primary, Gallenne, Alexandre, primary, Guerlet, Thibaut, primary, Haubois, Xavier, primary, Ives, Derek, primary, Jakob, Gerd, primary, Meister, Alexander, primary, Riquelme, Miguel, primary, Schuhler, Nicolas, primary, Stephan, Christian, primary, Toledo, Pedro, primary, Tristam, Konrad, primary, Woillez, Julien, primary, Neumann, Udo, primary, Chelli, Alain, primary, Guitton, Florence, primary, Meisenheimer, Klaus, primary, Pichon, Bernard, primary, Spang, Alain, primary, Varga, Jozsef, primary, Henning, Thomas, primary, Jaffe, Walter, primary, Pasquini, Luca, primary, Stee, Philippe, primary, Weigelt, Gerd, primary, Bettonvil, Felix, primary, Lehmitz, Michael, primary, and Beckmann, Udo, primary

Published
2018
Full Text
View/download PDF

37. Commissioning MATISSE: first results

Author

Cruzalèbes, Pierre, primary, Lagarde, Stéphane, primary, Robbe-Dubois, Sylvie, primary, Lopez, Bruno, primary, Berio, Philippe, primary, Millour, Florentin, primary, Allouche, Fatmé, primary, Fanteï-Caujolle, Yan, primary, Petrov, Romain, primary, Jaffe, Walter, primary, Matter, Alexis, primary, Meilland, Anthony, primary, Morel, Sebastien, primary, Paladini, Claudia, primary, Rivinius, Thomas, primary, Rousseau, Sylvain, primary, Varga, Jozsef, primary, Zins, Gérard, primary, Chelli, Alain, primary, Glidemann, Andreas, primary, and Schöller, Markus, primary

Published
2018
Full Text
View/download PDF

38. ELT high resolution spectrograph: phase-A software architecture study

Author

Di Marcantonio, Paolo, primary, Boisse, Isabelle, primary, Cirami, Roberto, primary, Cupani, Guido, primary, Di Varano, Igor, primary, Drass, Holger, primary, Figueira, Pedro, primary, Furlan de Souza, Marco Antonio, primary, Genoni, Matteo, primary, Landoni, Marco, primary, Li Causi, Gianluca, primary, Marquart, Thomas, primary, Mason, Elena, primary, Monteiro, Manuel, primary, Parro, Vanderlei, primary, Ribeiro Augusto, Sergio, primary, Rousseau, Sylvain, primary, Sanna, Nicoletta, primary, Shen, Tzu-Chiang, primary, Sosnowska, Danuta, primary, Sousa, Sérgio, primary, Xompero, Marco, primary, Marconi, Alessandro, primary, and Gonzalez, Oscar A., primary

Published
2018
Full Text
View/download PDF

39. ELT-HIRES, the high resolution spectrograph for the ELT: results from the Phase A study

Author

Di Marcantonio, Paolo, primary, Maiolino, Roberto, primary, Oliva, Ernesto, primary, Origlia, Livia, primary, Riva, Marco, primary, Valenziano, Luca, primary, Allende Prieto, Carlos, primary, Amado, Pedro, primary, Amate, Manuel, primary, Becerril, Santiago, primary, Bezawada, Naidu, primary, Boisse, Isabelle, primary, Bouchy, François, primary, Cabral, Alexandre, primary, Chazelas, Bruno, primary, Cirami, Roberto, primary, Coretti, Igor, primary, Cristiani, Stefano, primary, Cupani, Guido, primary, D'Odorico, Valentina, primary, de Souza, M. A. F., primary, Marconi, Alessandro, primary, de Castro Leão, Izan, primary, de Medeiros, José, primary, Di Varano, Igor, primary, Drass, Holger, primary, Figueira, Pedro, primary, Fragoso Lopez, Ana Belen, primary, Fynbo, Johan, primary, Genoni, Matteo, primary, González Hernández, Jonay, primary, Hughes, Ian, primary, Huke, Philipp, primary, Kjeldsen, Hans, primary, Korn, Andreas, primary, Landoni, Marco, primary, Liske, Jochen, primary, Lovis, Christophe, primary, Martins, Carlos, primary, Mason, Elena, primary, Monteiro, Manuel, primary, Morris, Timothy J., primary, Niedzielski, Andrzej, primary, Pallé, Enric, primary, Parr-Burman, Phil, primary, Pepe, Francesco, primary, Piskunov, Nikolai, primary, Rasilla, José Luis, primary, Rebolo-López, Rafael, primary, Rousseau, Sylvain, primary, Sanna, Nicoletta, primary, Santos, Nuno, primary, Shen, Tzu-Chiang, primary, Sortino, Francesca, primary, Sosnowska, Danuta, primary, Sousa, Sergio, primary, Stempels, Eric, primary, Strassmeier, Klaus G., primary, Tenegi, Fabio, primary, Tozzi, Andrea, primary, Udry, Stéphane, primary, Vanzi, Leonardo, primary, Weber, Michael, primary, Woche, Manfred, primary, Xompero, Marco, primary, Zackrisson, Erik, primary, Augusto, Sergio Ribeiro, primary, Parro, Vanderlei Cunha, primary, Murray, Graham, primary, Rees, Phil, primary, Haehnelt, Martin, primary, and Marquart, Thomas, primary

Published
2018
Full Text
View/download PDF

40. Olfactory stem cells reveal MOCOS as a new player in autism spectrum disorders

Author

Féron, François-Xavier, Gepner, B, Lacassagne, E, Stephan, S, Mesnage, M, Blanchard, M, Boulanger, N, Tardif, C, Devèze, A, Rousseau, Sylvain, Suzuki, K, Belmonte, Jc, Khrestchatisky, M, Nivet, E, Erard-Garcia, M, Neurobiologie des interactions cellulaires et neurophysiopathologie - NICN (NICN), Institut National de la Recherche Agronomique (INRA)-Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Centre d'Investigations Cliniques en Biothérapie (CBT 1409), INSERM, Centre de recherche en neurobiologie - neurophysiologie de Marseille (CRN2M), Aix Marseille Université (AMU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Technologies avancées pour le génôme et la clinique (TAGC), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre de Recherche en Psychologie de la Connaissance, du Langage et de l'Émotion (PsyCLÉ), Aix Marseille Université (AMU), Département ORL, Assistance Publique - Hôpitaux de Marseille (APHM), Département Anesthésie, Gene Expression Laboratory, The Salk Institute for Biological Studies, Université de la Méditerranée - Aix-Marseille 2-Centre National de la Recherche Scientifique (CNRS), Systèmes d'élevage méditerranéens et tropicaux (UMR SELMET), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Réponse immunitaire et developpement chez les insectes (RIDI - UPR 9002), Institut de biologie moléculaire et cellulaire (IBMC), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service d'ORL, CHU Nord, Laboratoire de Biomécanique Appliquée (LBA UMR T24), Aix Marseille Université (AMU)-Université Gustave Eiffel-Aix Marseille Université (AMU)-Université Gustave Eiffel, Neurobiologie intégrative et adaptative (NIA), Université de Provence - Aix-Marseille 1-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-Université de la Méditerranée - Aix-Marseille 2, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Université de Strasbourg (UNISTRA)-Institut de biologie moléculaire et cellulaire (IBMC), Université de Strasbourg (UNISTRA)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Aix Marseille Université (AMU)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Aix Marseille Université (AMU)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR), Institut de biologie et chimie des protéines [Lyon] (IBCP), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Aix Marseille Université (AMU)-Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-Aix Marseille Université (AMU), and Tardif, Carole

Subjects
Adult, Male, Autism Spectrum Disorder, [SDV]Life Sciences [q-bio], autism spectrum disorders, [SHS.PSY]Humanities and Social Sciences/Psychology, MOCOS, Olfactory Receptor Neurons, [SHS.PSY] Humanities and Social Sciences/Psychology, Mice, Olfactory Mucosa, stem cells, Animals, Humans, [SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], neurotransmission, Caenorhabditis elegans, ComputingMilieux_MISCELLANEOUS, Mice, Inbred C57BL, Sulfurtransferases, autism spectrum disorders, neurotransmission , MOCOS, stem cells, [SCCO.PSYC] Cognitive science/Psychology, [SCCO.PSYC]Cognitive science/Psychology, Original Article, Female, [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC], France
Abstract

International audience; With an onset under the age of 3 years, autism spectrum disorders (ASDs) are now understood as diseases arising from pre-and/or early postnatal brain developmental anomalies and/or early brain insults. To unveil the molecular mechanisms taking place during the misshaping of the developing brain, we chose to study cells that are representative of the very early stages of ontogenesis, namely stem cells. Here we report on MOlybdenum COfactor Sulfurase (MOCOS), an enzyme involved in purine metabolism, as a newly identified player in ASD. We found in adult nasal olfactory stem cells of 11 adults with ASD that MOCOS is downregulated in most of them when compared with 11 age-and gender-matched control adults without any neuropsychiatric disorders. Genetic approaches using in vivo and in vitro engineered models converge to indicate that altered expression of MOCOS results in neurotransmission and synaptic defects. Furthermore, we found that MOCOS misexpression induces increased oxidative-stress sensitivity. Our results demonstrate that altered MOCOS expression is likely to have an impact on neurodevelopment and neurotransmission, and may explain comorbid conditions, including gastrointestinal disorders. We anticipate our discovery to be a fresh starting point for the study on the roles of MOCOS in brain development and its functional implications in ASD clinical symptoms. Moreover, our study suggests the possible development of new diagnostic tests based on MOCOS expression, and paves the way for drug screening targeting MOCOS and/or the purine metabolism to ultimately develop novel treatments in ASD.

Published
2016

41. Rendu de Monte Carlo Elastique

Author

Rousseau, Sylvain, Boubekeur, Tamy, Télécom Paristech, Admin, Image, Modélisation, Analyse, GEométrie, Synthèse (IMAGES), Laboratoire Traitement et Communication de l'Information (LTCI), Institut Mines-Télécom [Paris] (IMT)-Télécom Paris-Institut Mines-Télécom [Paris] (IMT)-Télécom Paris, Département Traitement du Signal et des Images (TSI), Télécom ParisTech-Centre National de la Recherche Scientifique (CNRS), and Centre National de la Recherche Scientifique (CNRS)-Télécom ParisTech

Subjects
[STAT.AP]Statistics [stat]/Applications [stat.AP], rendu de Monte Carlo, [INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing, cloud computing, [INFO.INFO-GR] Computer Science [cs]/Graphics [cs.GR], calcul distribué, [INFO.INFO-GR]Computer Science [cs]/Graphics [cs.GR], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [STAT.AP] Statistics [stat]/Applications [stat.AP], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], informatique graphique, [INFO.INFO-DC]Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], synthèse d'image
Abstract

National audience; La synthèse d'images photoréalistes est un processus de simulation du transport de la lumière dans une scène tridimensionnelle qui est extrêmement coûteux en temps de calcul. En particulier, l'émergence du rendu basé physique dans l'industrie, principalement effectué à l'aide de la méthode du lancer de rayons de Monte Carlo, impose l'utilisation de fermes de calcul dédiées toujours plus puissantes, et ne s'accommode de scènes au contenu complexe qu'au prix de temps d'exécution souvent prohibitifs dans un contexte industriel. L'architecture de ces fermes passe de plus difficilement à l'échelle à chaque évolution majeure du critère de qualité attendu en production. Dans ce contexte, l'exploitation de ressources de calculs différentes, non dédiées mais massive, apparait comme une piste sérieuse pour la génération d'images de synthèse toujours plus précises et riches de contenu. Dans cet article, nous ébauchons un système de rendu conçu pour exploiter les grands flottes de machines hétérogênes, telles que celles présentes dans les grandes infrastructures informatiques publiques ou privées, avec pour but d'exploiter au maximum le temps de calcul disponible en conservant la généricité de déploiement du cloud computing. Ces flottes ont souvent pour particularité de représenter des clusters de taille importante mais composés de machines de puissances trés variables et exploitant des réseaux disposant d'une faible bande passante et d'une forte latence. Certaines, notamment dans l'industrie du web, prennent la forme de clusters principalements conçus pour effectuer de l'apprentissage automatique sur de grande masses de données et leur architecture matérielle n'est pas adaptée, en général, au calcul en synthèse d'image. Nous présentons ici une méthode permettant d'exploiter efficacement la puissance de ces deux types d'architectures matérielles.

Published
2016

43. Apprentissage de dictionnaire pour un modèle d'apparence parcimonieux en suivi visuel

Author

Rousseau, Sylvain, Garnier, Christelle, Chainais, Pierre, Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 (CRIStAL), Centrale Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Centrale Lille, Institut TELECOM/TELECOM Lille1, and Institut Mines-Télécom [Paris] (IMT)

Subjects
[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
Abstract

National audience; This paper presents a novel approach to visual object tracking based on particle filtering. The appearance of the target object is described by a sparse representation provided by dictionary learning, which leads to a model of reduced dimension. The likelihood of a candidate region is built on a similarity measure which can be interpreted as the result of a matched filter in the new representation space formed by the dictionary. Thus it can optimally detect a set of reference patches extracted from the target at known positions in the candidate region. Experimental validation shows the efficiency and the robustness of the proposed approach.; Cet article présente une nouvelle approche pour le suivi visuel par filtrage particulaire. L'apparence de l'objet cible est décrite par une représentation parcimonieuse fournie par apprentissage de dictionnaire, ce qui permet de créer un modèle de dimension réduite. La vraisemblance d'une région candidate est construite à partir d'une mesure de similarité qui s'interprète comme le résultat d'un filtrage adapté dans le nouvel espace de représentation formé par le dictionnaire. Cette approche permet de détecter de manière optimale la présence de l'ensemble des patchs de référence extraits de la cible aux positions considérées dans la région candidate. La validation expérimentale montre l'efficacité et la robustesse de l'approche proposée.

Published
2015

44. Commissioning MATISSE: first results.

Author

Petrov, Romain G., Allouche, Fatmé, Berio, Philippe, Chelli, Alain, Cruzalèbes, Pierre, Fanteï, Yan, Jaffe, Walter, Glindemann, Andreas, Lagarde, Stéphane, Lopez, Bruno, Matter, Alexis, Meilland, Antony, Millour, Florentin, Morel, Sebastien, Paladini, Claudia, Rivinius, Thomas, Robbe-Dubois, Sylvie, Rousseau, Sylvain, Schöller, Markus, and Varga, Jozsef

Published
2018
Full Text
View/download PDF

46. Détection de points d'intérêt par acquisition compressée dans une image multispectrale

Author

Rousseau, Sylvain, SIC (XLIM-SIC), Université de Poitiers-XLIM (XLIM), Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS)-Université de Limoges (UNILIM)-Centre National de la Recherche Scientifique (CNRS), Université de Poitiers, and Philippe Carré(philippe.carre@univ-poitiers.fr)

Subjects
Bregman algorithms, signature detection, multispectral image, acquisition compressée, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, pattern detection, image multispectrale, algorithmes de Bregman, détection de signatures, détection de motifs, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, compressed sensing
Abstract

Multi- and hyper-spectral sensors generate a huge stream of data. A way around this problem is to use a compressive acquisition of the multi- and hyper-spectral object. The object is then reconstructed when needed. The next step is to avoid this reconstruction and to work directly with compressed data to achieve a conventional treatment on an object of this nature. After introducing a first approach using Riemannian tools to perform edge detection in multispectral image, we present the principles of the compressive sensing and algorithms used to solve its problems. Then we devote an entire chapter to the detailed study of one of them, Bregman type algorithms which by their flexibility and efficiency will allow us to solve the minimization encountered later. We then focuses on the detection of signatures in a multispectral image relying on an original algorithm of Guo and Osher based on minimizing $L_1$. This algorithm is generalized in connection with the acquisition compressed. A second generalization will help us to achieve the pattern detection in a multispectral image. And finally, we introduce new matrices of measures that greatly simplifies calculations while maintaining a good quality of measurements.; Les capteurs multi- et hyper-spectraux génèrent un énorme flot de données. Un moyen de contourner cette difficulté est de pratiquer une acquisition compressée de l'objet multi- et hyper-spectral. Les données sont alors directement compressées et l'objet est reconstruit lorsqu'on en a besoin. L'étape suivante consiste à éviter cette reconstruction et à travailler directement avec les données compressées pour réaliser un traitement classique sur un objet de cette nature. Après avoir introduit une première approche qui utilise des outils riemanniens pour effectuer une détection de contours dans une image multispectrale, nous présentons les principes de l'acquisition compressée et différents algorithmes utilisés pour résoudre les problèmes qu'elle pose. Ensuite, nous consacrons un chapitre entier à l'étude détaillée de l'un d'entre eux, les algorithmes de type Bregman qui, par leur flexibilité et leur efficacité vont nous permettre de résoudre les minimisations rencontrées plus tard. On s'intéresse ensuite à la détection de signatures dans une image multispectrale et plus particulièrement à un algorithme original du Guo et Osher reposant sur une minimisation $L_1$. Cet algorithme est généralisé dans le cadre de l'acquisition compressée. Une seconde généralisation va permettre de réaliser de la détection de motifs dans une image multispectrale. Et enfin, nous introduirons de nouvelles matrices de mesures qui simplifie énormément les calculs tout en gardant de bonnes qualités de mesures.

Published
2013

49. Automesure tensionnelle pratique en soins primaires: étude MEGAMET enquête téléphonique nationale auprès de 546 médecins généralistes de mai à août 2004

Author

Rousseau, Sylvain, Université Henri Poincaré - Nancy 1 (UHP), UHP - Université Henri Poincaré, and Jean-Marc Boivin

Subjects
Éducation des patients, Pression artérielle-Mesure ambulatoire, [SDV]Life Sciences [q-bio], Thèse d'exercice de médecine, Non disponible / Not available
Abstract

Background: the ESH guidelines and HAS 2005 guidelines recommend the use of home blood pressure monitoring (HBPM) for the management of arterial hypertension.Objectives : to evaluate the percentage of General Practitioners (GPs) using HBPM and compare what they do with what the international guidelines recommend. Method : national phone survey (with a 14-item questionnaire), in which 546 GPs were included between May and August 2004. Results : 511 GPs answered. 30% of GPs did not use HBPM, because of method unreliability (62%), patient's anxiety (67%) and technical difficulties (30%).70% ofGPs used HBPM, 35% rarely or very occasionally, 35% often or as often as possible. Recommended measurement guidelines were hardly followed. Only 4% of GPs had 3 consecutive morning and evening measurements done for at least 3 days. Conclusion : French GPs rarely used HBPM and proper implementation of guidelines was poor in 2004. Multifaceted interventions aimed at educating GPs and patients about the use of HBPM are necessary to enhance blood pressure monitoring and improve the compliance of patients suffering from hypertension to HBPM.; Prérequis: les recommandations de l'ESH et de la HAS 2005 conseillent l'utilisation de l'automesure tensionnelle (AMT) dans la prise en charge de l'hypertension artérielle (HTA). Obiectifs : évaluer la proportion de médecins généralistes (MG) qui pratiquent l'AMT et comparer leur pratique aux recommandations internationales. Méthode : enquête nationale auprès de 546 MG entre mai et août 2004. Questionnaire téléphonique composé de 14 items. Résultats : 511 MG ont répondu. 30% des MG n'utilisent pas l'AMT, en raison de la non-fiabilité de la méthode (62%), du caractère anxiogène de l'AMT (67%), de difficultés techniques (30%). 70% des MG utilisent l'AMT : 35% rarement ou exceptionnellement, 35% souvent ou le plus souvent possible. Les protocoles de mesure recommandés sont peu suivis. Seuls 4 % font réaliser 3 mesures consécutives matin et soir pendant au moins 3 jours. Conclusion : la pratique de l'AMT par les MG français en 2004 est peu répandue et le respect des recommandations est médiocre. Des interventions multifactorielles sont nécessaires pour former les MG et les patients à l'AMT afin d'améliorer le contrôle tensionnel et l'observance des patients hypertendus.

Published
2007

Catalog

Books, media, physical & digital resources
See catalog results