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David Lipshutz
David Lipshutz
Center for Computational Neuroscience, Flatiron Institute
Verified email at flatironinstitute.org - Homepage
Title
Cited by
Cited by
Year
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
40*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
242021
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
202020
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
182020
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
152015
Open problem—Load balancing using delayed information
D Lipshutz
Stochastic Systems 9 (3), 305-306, 2019
132019
Exit time asymptotics for small noise stochastic delay differential equations
D Lipshutz
Discrete & Continuous Dynamical Systems - A 38 (6), 3099-3138, 2018
132018
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
122018
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
112021
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
112019
Biologically plausible single-layer networks for nonnegative independent component analysis
D Lipshutz, C Pehlevan, DB Chklovskii
Biological cybernetics 116 (5), 557-568, 2022
10*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
102018
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
92023
Interneurons accelerate learning dynamics in recurrent neural networks for statistical adaptation
D Lipshutz, C Pehlevan, DB Chklovskii
International Conference on Learning Representations, 2023
92023
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
72020
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
62023
Adaptive whitening with fast gain modulation and slow synaptic plasticity
L Duong, E Simoncelli, D Chklovskii, D Lipshutz
Advances in Neural Information Processing Systems 36, 2023
52023
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
42022
Customer-server population dynamics in heavy traffic
R Atar, P Karmakar, D Lipshutz
Stochastic Systems 12 (1), 68-91, 2022
42022
A Monte Carlo method for estimating sensitivities of reflected diffusions in convex polyhedral domains
D Lipshutz, K Ramanan
Stochastic Systems 9 (2), 101-140, 2019
42019
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Articles 1–20