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Proceedings of the National Academy of Sciences of the United States of America|June 24, 2024
Representations and generalization in artificial and brain neural networksQianyi Li, Ben Sorscher, Haim Sompolinsky
Proceedings of the National Academy of Sciences of the United States of America|October 17, 2022
Neural representational geometry underlies few-shot concept learningBen Sorscher, Surya Ganguli, Haim Sompolinsky
Proceedings of the National Academy of Sciences of the United States of America|February 6, 2026
Order parameters and phase transitions of continual learning in deep neural networksHaozhe Shan, Qianyi Li, Haim Sompolinsky
Current Opinion in Neurobiology|March 8, 2014
Computational neuroscience: beyond the local circuitHaim Sompolinsky
Danish Medical Journal|June 7, 2024
Deciphering the mysteries of the neural codeHaim Sompolinsky
Neural Computation|June 15, 2006
Implications of neuronal diversity on population codingMaoz Shamir, Haim Sompolinsky
Neural Computation|May 8, 2004
Nonlinear population codesMaoz Shamir, Haim Sompolinsky
Annual Review of Neuroscience|April 10, 2012
Compressed sensing, sparsity, and dimensionality in neuronal information processing and data analysisSurya Ganguli, Haim Sompolinsky
Scientific Reports|December 17, 2022
Associative memory of structured knowledgeJulia Steinberg, Haim Sompolinsky
Physical Review. E|January 21, 2023
Minimum perturbation theory of deep perceptual learningHaozhe Shan, Haim Sompolinsky
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