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Haim Sompolinsky

Showing results (51-60 of 66) with videos related to

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The Journal of Neuroscience : the Official Journal of the Society for Neuroscience|April 10, 2003
On the transmission of rate code in long feedforward networks with excitatory-inhibitory balanceVladimir Litvak, Haim Sompolinsky, Idan Segev, et al.
Physical Review. E|January 15, 2022
Predicting the outputs of finite deep neural networks trained with noisy gradientsGadi Naveh, Oded Ben David, Haim Sompolinsky, et al.
Nature Communications|February 8, 2020
Separability and geometry of object manifolds in deep neural networksUri Cohen, SueYeon Chung, Daniel D Lee, et al.
Journal of Cognitive Neuroscience|June 24, 2015
Evidence of Change of Intention in Picking SituationsAriel Furstenberg, Assaf Breska, Haim Sompolinsky, et al.
Neural Computation|August 28, 2018
Learning Data Manifolds with a Cutting Plane MethodSueYeon Chung, Uri Cohen, Haim Sompolinsky, et al.
Journal of Neurophysiology|October 12, 2007
Adaptation and information transmission in fly motion detectionMoshe N Safran, Virginia L Flanagin, Alexander Borst, et al.
Neuron|April 29, 2014
Learning precisely timed spikesRaoul-Martin Memmesheimer, Ran Rubin, Bence P Olveczky, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 21, 2025
Interactions between long- and short-term synaptic plasticity transform temporal neural representations into spatialQiang Yu, Misha Tsodyks, Haim Sompolinsky, et al.
Nature|August 12, 2021
Locally ordered representation of 3D space in the entorhinal cortexGily Ginosar, Johnatan Aljadeff, Yoram Burak, et al.
Neuron|November 22, 2016
The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical NetworksItamar D Landau, Robert Egger, Vincent J Dercksen, et al.
Pageof 7

Showing results (51-60 of 66) with videos related to

Sort By:
Pageof 7
The Journal of Neuroscience : the Official Journal of the Society for Neuroscience|April 10, 2003
On the transmission of rate code in long feedforward networks with excitatory-inhibitory balanceVladimir Litvak, Haim Sompolinsky, Idan Segev, et al.
Physical Review. E|January 15, 2022
Predicting the outputs of finite deep neural networks trained with noisy gradientsGadi Naveh, Oded Ben David, Haim Sompolinsky, et al.
Nature Communications|February 8, 2020
Separability and geometry of object manifolds in deep neural networksUri Cohen, SueYeon Chung, Daniel D Lee, et al.
Journal of Cognitive Neuroscience|June 24, 2015
Evidence of Change of Intention in Picking SituationsAriel Furstenberg, Assaf Breska, Haim Sompolinsky, et al.
Neural Computation|August 28, 2018
Learning Data Manifolds with a Cutting Plane MethodSueYeon Chung, Uri Cohen, Haim Sompolinsky, et al.
Journal of Neurophysiology|October 12, 2007
Adaptation and information transmission in fly motion detectionMoshe N Safran, Virginia L Flanagin, Alexander Borst, et al.
Neuron|April 29, 2014
Learning precisely timed spikesRaoul-Martin Memmesheimer, Ran Rubin, Bence P Olveczky, et al.
Proceedings of the National Academy of Sciences of the United States of America|November 21, 2025
Interactions between long- and short-term synaptic plasticity transform temporal neural representations into spatialQiang Yu, Misha Tsodyks, Haim Sompolinsky, et al.
Nature|August 12, 2021
Locally ordered representation of 3D space in the entorhinal cortexGily Ginosar, Johnatan Aljadeff, Yoram Burak, et al.
Neuron|November 22, 2016
The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical NetworksItamar D Landau, Robert Egger, Vincent J Dercksen, et al.
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