29 results on '"Scherr, Franz"'
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2. Self-Supervised Learning Through Efference Copies
3. 2022 Roadmap on Neuromorphic Computing and Engineering
4. Current State and Future Directions for Learning in Biological Recurrent Neural Networks: A Perspective Piece
5. Reservoirs learn to learn
6. Neuromorphic Hardware learns to learn
7. Biologically inspired alternatives to backpropagation through time for learning in recurrent neural nets
8. Reservoirs Learn to Learn
9. Modeling circuit mechanisms of opposing cortical responses to visual flow perturbations
10. Task success in trained spiking neuronal network models coincides with emergence of cross-stimulus-modulated inhibition
11. Data-based large-scale models provide a window into the organization of cortical computations
12. A solution to the learning dilemma for recurrent networks of spiking neurons
13. Competition between bottom-up visual input and internal inhibition generates error neurons in a model of the mouse primary visual cortex
14. Making neuromorphic the main stream of AI
15. A data-based large-scale model for primary visual cortex enables brain-like robust and versatile visual processing
16. 2022 roadmap on neuromorphic computing and engineering
17. Current State and Future Directions for Learning in Biological Recurrent Neural Networks: A Perspective Piece
18. Anatomical and neurophysiological data on primary visual cortex suffice for reproducing brain-like robust multiplexing of visual function
19. Analysis of the computational strategy of a detailed laminar cortical microcircuit model for solving the image-change-detection task
20. A data-based large-scale model for primary visual cortex enables brain-like robust and versatile visual processing.
21. PREDICTION ERROR COMPUTATION IN CORTICAL NEURONS VIA COMPETITION BETWEEN BOTTOM-UP VISUAL INPUT AND RECURRENT INHIBITION
22. Visualizing a joint future of neuroscience and neuromorphic engineering
23. Revisiting the role of synaptic plasticity and network dynamics for fast learning in spiking neural networks
24. One-shot learning with spiking neural networks
25. Learning-to-Learn in Data-Based Columnar Models of Visual Cortex
26. Spike-based agents for multi-armed bandits
27. A solution to the learning dilemma for recurrent networks of spiking neurons
28. Neuromorphic Hardware Learns to Learn
29. Inhibition of Mg, Ca-ATPase from E. coli by Ruthenium Red
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