Haim Sompolinsky - researchr alias

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Viewing Publication 1 - 35 from 35

2023

Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural ArchitecturesNaoki Hiratani, Haim Sompolinsky. neco, 35(2):105-155, February 2023. [doi]

2022

The spectrum of covariance matrices of randomly connected recurrent neuronal networks with linear dynamicsYu Hu, Haim Sompolinsky. ploscb, 18(7), 2022. [doi]

Globally Gated Deep Linear NetworksQianyi Li, Haim Sompolinsky. nips 2022: [doi]

A theory of weight distribution-constrained learningWeishun Zhong, Ben Sorscher, Daniel Lee, Haim Sompolinsky. nips 2022: [doi]

2020

High-dimensional dynamics of generalization error in neural networksMadhu S. Advani, Andrew M. Saxe, Haim Sompolinsky. NN, 132:428-446, 2020. [doi]

2019

Functional diversity among sensory neurons from efficient coding principlesJulijana Gjorgjieva, Markus Meister, Haim Sompolinsky. ploscb, 15(11), 2019. [doi]

2018

Learning Data Manifolds with a Cutting Plane MethodSueYeon Chung, Uri Cohen, Haim Sompolinsky, Daniel D. Lee. neco, 30(10), 2018. [doi]

Coherent chaos in a recurrent neural network with structured connectivityItamar Daniel Landau, Haim Sompolinsky. ploscb, 14(12), 2018. [doi]

2017

Markov Transitions between Attractor States in a Recurrent Neural NetworkJeremy Bernstein, Ishita Dasgupta, David Rolnick, Haim Sompolinsky. aaaiss 2017: [doi]

2016

Optimal Architectures in a Solvable Model of Deep NetworksJonathan Kadmon, Haim Sompolinsky. nips 2016: 4781-4789 [doi]

2015

Evidence of Change of Intention in Picking SituationsAriel Furstenberg, Assaf Breska, Haim Sompolinsky, Leon Y. Deouell. jocn, 27(11):2133-2146, 2015. [doi]

2012

How the Brain Generates MovementUri Rokni, Haim Sompolinsky. neco, 24(2):289-331, 2012. [doi]

2011

Introducing the Human Brain ProjectHenry Markram, Karlheinz Meier, Thomas Lippert, Sten Grillner, Richard S. Frackowiak, Stanislas Dehaene, Alois Knoll, Haim Sompolinsky, Kris Verstreken, Javier DeFelipe, Seth Grant, Jean-Pierre Changeux, Alois Saria. procedia, 7:39-42, 2011. [doi]

2010

Short-term memory in neuronal networks through dynamical compressed sensingSurya Ganguli, Haim Sompolinsky. nips 2010: 667-675 [doi]

Inferring Stimulus Selectivity from the Spatial Structure of Neural Network DynamicsKanaka Rajan, L. Abbott, Haim Sompolinsky. nips 2010: 1975-1983 [doi]

2009

Stimulus-Dependent Correlations in Threshold-Crossing Spiking NeuronsYoram Burak, Sam Lewallen, Haim Sompolinsky. neco, 21(8):2269-2308, 2009. [doi]

2006

Implications of Neuronal Diversity on Population CodingMaoz Shamir, Haim Sompolinsky. neco, 18(8):1951-1986, 2006. [doi]

2004

Nonlinear Population CodesMaoz Shamir, Haim Sompolinsky. neco, 16(6):1105-1136, 2004. [doi]

2003

Rate Models for Conductance-Based Cortical Neuronal NetworksOren Shriki, David Hansel, Haim Sompolinsky. neco, 15(8):1809-1841, 2003. [doi]

2001

Correlation Codes in Neuronal PopulationsMaoz Shamir, Haim Sompolinsky. nips 2001: 277-284 [doi]

2000

An Information Maximization Approach to Overcomplete and Recurrent RepresentationsOren Shriki, Haim Sompolinsky, Daniel D. Lee. nips 2001: 612-618

1999

Algorithms for Independent Components Analysis and Higher Order StatisticsDaniel D. Lee, Uri Rokni, Haim Sompolinsky. nips 2000: 491-497 [doi]

1998

Learning a Continuous Hidden Variable Model for Binary DataDaniel D. Lee, Haim Sompolinsky. nips 1999: 515-521 [doi]

Chaotic Balanced State in a Model Of Cortical CircuitsCarl van Vreeswijk, Haim Sompolinsky. neco, 10(6):1321-1371, 1998.

The Effect of Correlations on the Fisher Information of Population CodesHyoungsoo Yoon, Haim Sompolinsky. nips 1999: 167-173 [doi]

1997

Traveling Waves and the Processing of Weakly Tuned Inputs in a Cortical Network ModuleRani Ben-Yishai, David Hansel, Haim Sompolinsky. jcns, 4(1):57-77, 1997.

1996

Chaos and synchrony in a model of a hypercolumn in visual cortexDavid Hansel, Haim Sompolinsky. jcns, 3(1):7-34, 1996. [doi]

Neural network models of perceptual learning of angle discriminationGermán Mato, Haim Sompolinsky. neco, 8(2):270-299, 1996.

1994

On-line Learning of DichotomiesN. Barkai, H. Sebastian Seung, Haim Sompolinsky. nips 1995: 303-310 [doi]

Segmentation by a Network of Oscillators with Stored MemoriesHaim Sompolinsky, Michail Tsodyks. neco, 6(4):642-657, 1994. [doi]

1993

Correlation Functions in a Large Stochastic NetworkIris Ginzburg, Haim Sompolinsky. nips 1994: 471-476 [doi]

Stimulus-Dependent Synchronization of Neuronal AssembliesE. R. Grannan, D. Kleinfeld, Haim Sompolinsky. neco, 5(4):550-569, 1993. [doi]

1992

Query by CommitteeH. Sebastian Seung, Manfred Opper, Haim Sompolinsky. colt 1992: 287-294 [doi]

Processing of Sensory Information by a Network of Oscillators with MemoryHaim Sompolinsky, Michail Tsodyks. IJNS, 3(Supplement):51-56, 1992. [doi]

1991

Learning Curves in Large Neural NetworksH. Sebastian Seung, Haim Sompolinsky, Naftali Tishby. colt 1991: 112-127 [doi]

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