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Haim Sompolinsky

Hebrew University of Jerusalem · IL
Area of research
Cognitive Neuroscience · Artificial Intelligence
Research interest
Research interests include Computer science, Neuroscience, Artificial intelligence, Sensory system, Artificial neural network, and Statistical physics.
h-index
citations
3,314
works
37
NIH funding
primary concept
email

Recent publications

Coding schemes in neural networks learning classification tasks
Nature Communications 2025cited by 5position: lastdoi
Interactions between long- and short-term synaptic plasticity transform temporal neural representations into spatial
Proceedings of the National Academy of Sciences 2025cited by 3position: middledoi
Unified theoretical framework for wide neural network learning dynamics
Physical review. E 2025cited by 1position: lastdoi
Simplified derivations for high-dimensional convex learning problems
SciPost Physics Lecture Notes 2025cited by 1position: lastdoi
Representations and generalization in artificial and brain neural networks
Proceedings of the National Academy of Sciences 2024cited by 28position: lastdoi
Statistical mechanics of deep learning
Journal of Statistical Mechanics Theory and Experiment 2024cited by 2position: lastdoi
Neural representational geometry underlies few-shot concept learning
Proceedings of the National Academy of Sciences 2022cited by 76position: lastdoi
The spectrum of covariance matrices of randomly connected recurrent neuronal networks with linear dynamics
PLoS Computational Biology 2022cited by 36position: lastdoi
Associative memory of structured knowledge
Scientific Reports 2022cited by 24position: lastdoi
Stochastic consolidation of lifelong memory
Scientific Reports 2022cited by 11position: lastdoi
Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural Architectures
Neural Computation 2022cited by 7position: lastdoi
Minimum perturbation theory of deep perceptual learning
Physical review. E 2022cited by 6position: lastdoi
Locally ordered representation of 3D space in the entorhinal cortex
Nature 2021cited by 135position: middledoi
New role for circuit expansion for learning in neural networks
Physical review. E 2021cited by 3position: lastdoi
Separability and geometry of object manifolds in deep neural networks
Nature Communications 2020cited by 182position: lastdoi
Neural Correlates of Learning Pure Tones or Natural Sounds in the Auditory Cortex
Frontiers in Neural Circuits 2020cited by 45position: middledoi
Young adult-born neurons improve odor coding by mitral cells
Nature Communications 2020cited by 38position: middledoi
Functional diversity among sensory neurons from efficient coding principles
PLoS Computational Biology 2019cited by 36position: lastdoi
Brain-wide Organization of Neuronal Activity and Convergent Sensorimotor Transformations in Larval Zebrafish
Neuron 2018cited by 236position: middledoi
Classification and Geometry of General Perceptual Manifolds
Physical Review X 2018cited by 132position: lastdoi
Coherent chaos in a recurrent neural network with structured connectivity
PLoS Computational Biology 2018cited by 70position: lastdoi
Learning Data Manifolds with a Cutting Plane Method
Neural Computation 2018cited by 11position: middledoi
Optimal Degrees of Synaptic Connectivity
Neuron 2017cited by 407position: middledoi
Balanced excitation and inhibition are required for high-capacity, noise-robust neuronal selectivity
Proceedings of the National Academy of Sciences 2017cited by 131position: lastdoi
From Whole-Brain Data to Functional Circuit Models: The Zebrafish Optomotor Response
Cell 2016cited by 340position: middledoi
The Impact of Structural Heterogeneity on Excitation-Inhibition Balance in Cortical Networks
Neuron 2016cited by 139position: lastdoi
Linear readout of object manifolds
Physical review. E 2016cited by 43position: lastdoi
Optimal Architectures in a Solvable Model of Deep Networks
German Neuroinformatics Node 2016cited by 26position: lastdoi
Evidence of Change of Intention in Picking Situations
Journal of Cognitive Neuroscience 2015cited by 27position: middledoi
Sparseness and Expansion in Sensory Representations
Neuron 2014cited by 289position: lastdoi

Grants

No grants ingested yet.

Frequent collaborators

Daniel D. Lee · Samsung (United States)4 papers (2016–2020)SueYeon Chung · Harvard University4 papers (2016–2020) · 3 papers (2022–2024)L. F. Abbott · Columbia University3 papers (2014–2017)Itamar Daniel Landau · Hebrew University of Jerusalem3 papers (2016–2020)Markus Meister · California Institute of Technology3 papers (2013–2019)Florian Engert · Harvard University2 papers (2016–2018)Adi Mizrahi · Hebrew University of Jerusalem2 papers (2020–2020)Yu Hu · Jinan University2 papers (2018–2022)Uri Cohen · Hebrew University of Jerusalem2 papers (2018–2020)Qianyi Li · Ningbo University2 papers (2024–2025)Julia Steinberg · Princeton University2 papers (2021–2022)Ran Rubin · Hebrew University of Jerusalem2 papers (2014–2017)Julijana Gjorgjieva · Technical University of Munich2 papers (2014–2019)Ido Maor · Hebrew University of Jerusalem2 papers (2020–2020)Surya Ganguli · Stanford University2 papers (2012–2022)Robert Gütig · Hebrew University of Jerusalem2 papers (2013–2025)Jonathan Kadmon · Hebrew University of Jerusalem1 papers (2016–2016)Nimrod Shaham · Hebrew University of Jerusalem1 papers (2022–2022)Haran Shani-Narkiss · Hebrew University of Jerusalem1 papers (2020–2020)