Searching for authors named "Haim Sompolinsky" – sorted by Relevance.
10 documents found, showing 1 through 10.
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Learning input correlations through nonlinear temporally asymmetric hebbian plasticity
- … * R. Aharonov, 2 * S. Rotter, 1 and Haim Sompolinsky 2,3 1Institute of Biology III, University…
- Cited by 24 (0 self) – Add To MetaCart
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The Effect of Correlations on the Fisher Information of Population Codes
- …@(email omitted); Haim Sompolinsky haim@(email omitted); Racah Institute of Physics and Center for Neural Computation…
- Cited by 8 (1 self) – Add To MetaCart
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Correlation Codes in Neuronal Populations
- …Correlation Codes in Neuronal Populations Maoz Shamir and Haim Sompolinsky Racah Institute…
- Cited by 3 (0 self) – Add To MetaCart
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Theory of Correlations in Stochastic Neural Networks
- … Beverly and Raymond Sackler Faculty of Exact Sciences Tel-Aviv University, Tel-Aviv 69978, Israel Haim…
- Cited by 13 (4 self) – Add To MetaCart
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Rate Models for Conductance Based Cortical Neuronal Networks
- …Rate Models for Conductance Based Cortical Neuronal Networks Oren Shriki 1 , Haim Sompolinsky 1…
- Cited by 4 (0 self) – Add To MetaCart
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An Information Maximization Approach to Overcomplete and Recurrent Representations
- … and Haim Sompolinsky Racah Institute of Physics and Center for Neural Computation Hebrew University…
- Cited by 4 (2 self) – Add To MetaCart
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Feature Selectivity in a Cortical Module with Short-Range Excitation
- …Feature Selectivity in a Cortical Module with Short-Range Excitation David Hansel y and Haim…
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Majority Voting in the Presence of Random Voters
- …Majority Voting in the Presence of Random Voters Danny Dolev 1 Dror G. Feitelson 1 Haim…
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Bayesian Methods for Adaptive Models
- …, Sibusiso Sibisi, John Skilling, Haim Sompolinsky and Nick Weir. The comments of referees on chapter 4 were…
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Bayesian Methods for Adaptive Models
- …, Sibusiso Sibisi, John Skilling, Haim Sompolinsky and Nick Weir. The comments of referees on chapter 4 were…
- Cited by 125 (3 self) – Add To MetaCart
Showing 1 through 10.
