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Matthew Chalk

Showing results (1-10 of 14) with videos related to

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Journal of Neural Engineering|June 6, 2022
Human-in-the-loop optimization of visual prosthetic stimulationTristan Fauvel, Matthew Chalk
Current Opinion in Neurobiology|April 12, 2016
Efficiency turns the table on neural encoding, decoding and noiseSophie Deneve, Matthew Chalk
Neural Computation|June 20, 2013
Attention as reward-driven optimization of sensory processingMatthew Chalk, Iain Murray, Peggy Seriès
Plos One|April 15, 2021
Inferring the function performed by a recurrent neural networkMatthew Chalk, Gasper Tkacik, Olivier Marre
Proceedings of the National Academy of Sciences of the United States of America|December 21, 2017
Toward a unified theory of efficient, predictive, and sparse codingMatthew Chalk, Olivier Marre, Gašper Tkačik
Elife|July 8, 2016
Neural oscillations as a signature of efficient coding in the presence of synaptic delaysMatthew Chalk, Boris Gutkin, Sophie Denève
Proceedings of the National Academy of Sciences of the United States of America|August 14, 2023
Scalable Gaussian process inference of neural responses to natural imagesMatías A Goldin, Samuele Virgili, Matthew Chalk
Journal of Vision|October 2, 2010
Rapidly learned stimulus expectations alter perception of motionMatthew Chalk, Aaron R Seitz, Peggy Seriès
Plos Computational Biology|June 17, 2017
Sensory noise predicts divisive reshaping of receptive fieldsMatthew Chalk, Paul Masset, Sophie Deneve, et al.
Advances in Neural Information Processing Systems|July 10, 2024
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual ProsthesesJacob Granley, Tristan Fauvel, Matthew Chalk, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Journal of Neural Engineering|June 6, 2022
Human-in-the-loop optimization of visual prosthetic stimulationTristan Fauvel, Matthew Chalk
Current Opinion in Neurobiology|April 12, 2016
Efficiency turns the table on neural encoding, decoding and noiseSophie Deneve, Matthew Chalk
Neural Computation|June 20, 2013
Attention as reward-driven optimization of sensory processingMatthew Chalk, Iain Murray, Peggy Seriès
Plos One|April 15, 2021
Inferring the function performed by a recurrent neural networkMatthew Chalk, Gasper Tkacik, Olivier Marre
Proceedings of the National Academy of Sciences of the United States of America|December 21, 2017
Toward a unified theory of efficient, predictive, and sparse codingMatthew Chalk, Olivier Marre, Gašper Tkačik
Elife|July 8, 2016
Neural oscillations as a signature of efficient coding in the presence of synaptic delaysMatthew Chalk, Boris Gutkin, Sophie Denève
Proceedings of the National Academy of Sciences of the United States of America|August 14, 2023
Scalable Gaussian process inference of neural responses to natural imagesMatías A Goldin, Samuele Virgili, Matthew Chalk
Journal of Vision|October 2, 2010
Rapidly learned stimulus expectations alter perception of motionMatthew Chalk, Aaron R Seitz, Peggy Seriès
Plos Computational Biology|June 17, 2017
Sensory noise predicts divisive reshaping of receptive fieldsMatthew Chalk, Paul Masset, Sophie Deneve, et al.
Advances in Neural Information Processing Systems|July 10, 2024
Human-in-the-Loop Optimization for Deep Stimulus Encoding in Visual ProsthesesJacob Granley, Tristan Fauvel, Matthew Chalk, et al.
Pageof 2