HS
Haim Sompolinsky
Models, Neurologicalcond-mat.dis-nnq-bio.NCcs.LGneurosciencestat.MLNeural Networks, Computercond-mat.stat-mechcs.NEcs.AI
On Valency
published · living versionsW_naq97sba·v1 · currentpublished
Stimulus-Dependent Suppression of Chaos in Recurrent Neural Networks
with Kanaka Rajan, L F Abbott
1 version
Preprints & journals
164 papers in the corpus · 1989–2026Neural representational geometry of a joint code for stimulus category and category-independent features10.64898/2026.03.23.713692v3 · Tiberi, L., Sompolinsky, H.2026 · 0 citationsbioRxiv
Sparse Prototype Code Underlies Classification and Prediction Across Modalities2608.15632v1 · Yehonatan Avidan, Daniel D. Lee, Haim Sompolinsky2026 · 0 citationsarXiv
Unraveling the geometry of visual relational reasoning.42098214 · Shang, Jiaqi, Kreiman, Gabriel, Sompolinsky, Haim2026 · 0 citationsScientific reports. 2026;16(1)
Order parameters and phase transitions of continual learning in deep neural networks.41650219 · Shan, Haozhe, Li, Qianyi, Sompolinsky, Haim2026 · 3 citationsProceedings of the National Academy of Sciences of the United States of America. 2026;123(6):e2501899123
Diffusion-Inspired Masked Fine-Tuning for Knowledge Injection in Autoregressive LLMs2510.09885v6 · Xu Pan, Ely Hahami, Jingxuan Fan et al.2025 · 0 citationsarXiv
Unraveling the Geometry of Visual Relational Reasoning.40061119 · Shang, Jiaqi, Kreiman, Gabriel, Sompolinsky, Haim2026 · 0 citationsArXiv. 2025
Object manifold geometry across the mouse cortical visual hierarchy10.1101/2020.08.20.258798v5 · Froudarakis, E., Cohen, U., Diamantaki, M. et al.2020 · 48 citationsbioRxiv
Interactions between long- and short-term synaptic plasticity transform temporal neural representations into spatial.41269798 · Yu, Qiang, Tsodyks, Misha, Sompolinsky, Haim et al.2025 · 6 citationsProceedings of the National Academy of Sciences of the United States of America. 2025;122(47):e2426290122
Simplified derivations for high-dimensional convex learning problems2412.01110v5 · David G. Clark, Haim Sompolinsky2024 · 1 citationSciPost Phys. Lect. Notes 105 (2025)
Symmetries and continuous attractors in disordered neural circuits10.1101/2025.01.26.634933v2 · Clark, D. G., Abbott, L. F., Sompolinsky, H.2025 · 10 citationsbioRxiv
Unraveling the geometry of visual relational reasoning2502.17382v2 · Jiaqi Shang, Gabriel Kreiman, Haim Sompolinsky2025 · 0 citationsarXiv
Unified theoretical framework for wide neural network learning dynamics.40410999 · Avidan, Yehonatan, Li, Qianyi, Sompolinsky, Haim2025 · 1 citationPhysical review. E. 2025;111(4-2):045310
Coding schemes in neural networks learning classification tasks2406.16689v1 · Alexander van Meegen, Haim Sompolinsky2024 · 10 citationsarXiv
Connecting NTK and NNGP: A Unified Theoretical Framework for Wide Neural Network Learning Dynamics2309.04522v3 · Yehonatan Avidan, Qianyi Li, Haim Sompolinsky2023 · 2 citationsarXiv
Memorization and Knowledge Injection in Gated LLMs2504.21239v1 · Xu Pan, Ely Hahami, Zechen Zhang et al.2025 · 0 citationsarXiv
When narrower is better: the narrow width limit of Bayesian parallel branching neural networks2407.18807v3 · Zechen Zhang, Haim Sompolinsky2024 · 0 citationsarXiv
Order parameters and phase transitions of continual learning in deep neural networks2407.10315v2 · Haozhe Shan, Qianyi Li, Haim Sompolinsky2024 · 3 citationsarXiv
Dissecting the Interplay of Attention Paths in a Statistical Mechanics Theory of Transformers2405.15926v2 · Lorenzo Tiberi, Francesca Mignacco, Kazuki Irie et al.2024 · 3 citationsarXiv
Diverse capability and scaling of diffusion and auto-regressive models when learning abstract rules2411.07873v1 · Binxu Wang, Jiaqi Shang, Haim Sompolinsky2024 · 0 citationsarXiv
Effect of Aging on Change of Intention.31417383 · Furstenberg, Ariel, Dewar, Callum D, Sompolinsky, Haim et al.2024 · 3 citationsFrontiers in human neuroscience. 2019;13:264
Error monitoring when no errors are possible: Arbitrary free-choice decisions invoke error monitoring processes.37009217 · Furstenberg, Ariel, Sompolinsky, Haim, Deouell, Leon Y2024 · 6 citationsiScience. 2023;26(4):106373
Representations and generalization in artificial and brain neural networks.38913896 · Li, Qianyi, Sorscher, Ben, Sompolinsky, Haim2024 · 29 citationsProceedings of the National Academy of Sciences of the United States of America. 2024;121(27):e2311805121
Deciphering the mysteries of the neural code.38847414 · Sompolinsky, Haim2024 · 1 citationDanish medical journal. 2024;71(6)
Probing Biological and Artificial Neural Networks with Task-dependent Neural Manifolds2312.14285v1 · Michael Kuoch, Chi-Ning Chou, Nikhil Parthasarathy et al.2023 · 2 citationsarXiv
Optimal Quadratic Binding for Relational Reasoning in Vector Symbolic Neural Architectures.36543330 · Hiratani, Naoki, Sompolinsky, Haim2023 · 7 citationsNeural computation. 2023;35(2):105-155
Minimum perturbation theory of deep perceptual learning.36671118 · Shan, Haozhe, Sompolinsky, Haim2023 · 6 citationsPhysical review. E. 2022;106(6-1):064406
Associative memory of structured knowledge.36528630 · Steinberg, Julia, Sompolinsky, Haim2022 · 29 citationsScientific reports. 2022;12(1):21808
Globally Gated Deep Linear Networks2210.17449v2 · Qianyi Li, Haim Sompolinsky2022 · 3 citationsNeurIPS 2022
Associative memory of structured knowledge10.1101/2022.02.22.481380v5 · Steinberg, J., Sompolinsky, H.2022 · 29 citationsbioRxiv
A theory of learning with constrained weight-distribution2206.08933v2 · Weishun Zhong, Ben Sorscher, Daniel D Lee et al.2022 · 0 citationsarXiv
Neural representational geometry underlies few-shot concept learning.36251997 · Sorscher, Ben, Ganguli, Surya, Sompolinsky, Haim2022 · 80 citationsProceedings of the National Academy of Sciences of the United States of America. 2022;119(43):e2200800119
A Minimum Perturbation Theory of Deep Perceptual Learning10.1101/2021.10.05.463260v2 · Shan, H., Sompolinsky, H.2021 · 2 citationsbioRxiv
Soft-margin classification of object manifolds2203.07040v1 · Uri Cohen, Haim Sompolinsky2022 · 3 citationsPhys. Rev. E 106, 024126 (2022)
The spectrum of covariance matrices of randomly connected recurrent neuronal networks with linear dynamics.35862445 · Hu, Yu, Sompolinsky, Haim2022 · 44 citationsPLoS computational biology. 2022;18(7):e1010327
Stochastic consolidation of lifelong memory.35907920 · Shaham, Nimrod, Chandra, Jay, Kreiman, Gabriel et al.2022 · 15 citationsScientific reports. 2022;12(1):13107
Temporal support vectors for spiking neuronal networks2205.14544v1 · Ran Rubin, Haim Sompolinsky2022 · 0 citationsarXiv
Optimal quadratic binding for relational reasoning in vector symbolic neural architectures2204.07186v1 · Naoki Hiratani, Haim Sompolinsky2022 · 7 citationsarXiv
Temporal association in asymmetric neural networks.10033885 · Sompolinsky, Kanter2022 · 583 citationsPhysical review letters. 1986;57(22):2861-2864
Chaos in random neural networks.10039285 · Sompolinsky, Crisanti, Sommers2022 · 1,126 citationsPhysical review letters. 1988;61(3):259-262
Predicting the outputs of finite deep neural networks trained with noisy gradients2004.01190v3 · Gadi Naveh, Oded Ben-David, Haim Sompolinsky et al.2020 · 24 citationsarXiv
The spectrum of covariance matrices of randomly connected recurrent neuronal networks10.1101/2020.08.31.274936v2 · Hu, Y., Sompolinsky, H.2020 · 9 citationsbioRxiv
Locally ordered representation of 3D space in the entorhinal cortex.34381211 · Ginosar, Gily, Aljadeff, Johnatan, Burak, Yoram et al.2021 · 144 citationsNature. 2021;596(7872):404-409
Stochastic Consolidation of Lifelong Memory10.1101/2021.08.24.457446v1 · Shaham, N., Chandra, J., Kreiman, G. et al.2021 · 15 citationsbioRxiv
The Geometry of Concept Learning10.1101/2021.03.21.436284v2 · Sorscher, B., Ganguli, S., Sompolinsky, H.2021 · 10 citationsbioRxiv
A new role for circuit expansion for learning in neural networks2008.08653v2 · Julia Steinberg, Madhu Advani, Haim Sompolinsky2020 · 3 citationsPhys. Rev. E 103, 022404 (2021)
Young adult-born neurons improve odor coding by mitral cells.33203831 · Shani-Narkiss, H, Vinograd, A, Landau, I D et al.2020 · 37 citationsNature communications. 2020;11(1):5867
Properties of sparsely connected excitatory neural networks.9903143 · Barkai, Kanter, Sompolinsky2020 · 31 citationsPhysical review. A, Atomic, molecular, and optical physics. 1990;41(2):590-597
Willshaw model: Associative memory with sparse coding and low firing rates.9903293 · Golomb, Rubin, Sompolinsky2020 · 80 citationsPhysical review. A, Atomic, molecular, and optical physics. 1990;41(4):1843-1854
Cooperative dynamics in visual processing.9905051 · Sompolinsky, Golomb, Kleinfeld2020 · 240 citationsPhysical review. A, Atomic, molecular, and optical physics. 1991;43(12):6990-7011
Clustering in globally coupled phase oscillators.9907399 · Golomb, Hansel, Shraiman et al.2020 · 282 citationsPhysical review. A, Atomic, molecular, and optical physics. 1992;45(6):3516-3530
Career total: 262 works. 164 are in this corpus.Showing the 50 most recent.
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