| Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning S Qin, S Farashahi, D Lipshutz, AM Sengupta, DB Chklovskii, C Pehlevan Nature Neuroscience 26 (2), 339-349, 2023 | 25* | 2023 |
| A biologically plausible neural network for multichannel canonical correlation analysis D Lipshutz, Y Bahroun, S Golkar, AM Sengupta, DB Chklovskii Neural Computation 33 (9), 2309-2352, 2021 | 21 | 2021 |
| A simple normative network approximates local non-Hebbian learning in the cortex S Golkar, D Lipshutz, Y Bahroun, A Sengupta, D Chklovskii Advances in neural information processing systems 33, 7283-7295, 2020 | 19 | 2020 |
| A biologically plausible neural network for slow feature analysis D Lipshutz, C Windolf, S Golkar, D Chklovskii Advances in neural information processing systems 33, 14986-14996, 2020 | 17 | 2020 |
| Existence, uniqueness, and stability of slowly oscillating periodic solutions for delay differential equations with nonnegativity constraints D Lipshutz, RJ Williams SIAM Journal on Mathematical Analysis 47 (6), 4467-4535, 2015 | 15 | 2015 |
| Exit time asymptotics for small noise stochastic delay differential equations D Lipshutz Discrete & Continuous Dynamical Systems - A 38 (6), 3099-3138, 2018 | 12 | 2018 |
| Large deviations for the empirical measure of a diffusion via weak convergence methods P Dupuis, D Lipshutz Stochastic Processes and their Applications 128 (8), 2581-2604, 2018 | 12 | 2018 |
| Heavy traffic limits for join-the-shortest-estimated-queue policy using delayed information R Atar, D Lipshutz Mathematics of Operations Research 46 (1), 268-300, 2021 | 11 | 2021 |
| Open problem—Load balancing using delayed information D Lipshutz Stochastic Systems 9 (3), 305-306, 2019 | 11 | 2019 |
| Pathwise differentiability of reflected diffusions in convex polyhedral domains D Lipshutz, K Ramanan Annales de l’Institut Henri Poincaré-Probabilités et Statistiques 55 (3 …, 2019 | 11 | 2019 |
| Biologically plausible single-layer networks for nonnegative independent component analysis D Lipshutz, C Pehlevan, DB Chklovskii Biological Cybernetics 116 (5), 557-568, 2022 | 9* | 2022 |
| On directional derivatives of Skorokhod maps in convex polyhedral domains D Lipshutz, K Ramanan The Annals of Applied Probability 28 (2), 688-750, 2018 | 9 | 2018 |
| Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation D Lipshutz, C Pehlevan, DB Chklovskii International Conference on Learning Representations, 2023 | 7 | 2023 |
| Adaptive Whitening in Neural Populations with Gain-modulating Interneurons L Duong, D Lipshutz, D Heeger, D Chklovskii, EP Simoncelli International Conference on Machine Learning, 8902-8921, 2023 | 6* | 2023 |
| A biologically plausible neural network for local supervision in cortical microcircuits S Golkar, D Lipshutz, Y Bahroun, AM Sengupta, DB Chklovskii arXiv preprint arXiv:2011.15031, 2020 | 6 | 2020 |
| Normative framework for deriving neural networks with multicompartmental neurons and non-Hebbian plasticity D Lipshutz, Y Bahroun, S Golkar, AM Sengupta, DB Chklovskii PRX Life 1 (1), 013008, 2023 | 5 | 2023 |
| Customer-server population dynamics in heavy traffic R Atar, P Karmakar, D Lipshutz Stochastic Systems 12 (1), 68-91, 2022 | 4 | 2022 |
| An online algorithm for contrastive principal component analysis S Golkar, D Lipshutz, T Tesileanu, DB Chklovskii ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | 3 | 2023 |
| Biological Learning of Irreducible Representations of Commuting Transformations A Genkin, D Lipshutz, S Golkar, T Tesileanu, D Chklovskii Advances in Neural Information Processing Systems 35, 20838-20849, 2022 | 3 | 2022 |
| Sensitivity analysis for the stationary distribution of reflected Brownian motion in a convex polyhedral cone D Lipshutz, K Ramanan Mathematics of Operations Research 46 (2), 524-558, 2021 | 3 | 2021 |
Dmitri "Mitya" B. ChklovskiiCCN, Flatiron Institute, Simons Foundation and NYUVerified email at flatironinstitute.org
