| Acute off-target effects of neural circuit manipulations TM Otchy, SBE Wolff, JY Rhee, C Pehlevan, R Kawai, A Kempf, ... Nature 528 (7582), 358-363, 2015 | 384 | 2015 |
| Spectrum dependent learning curves in kernel regression and wide neural networks B Bordelon, A Canatar, C Pehlevan International Conference on Machine Learning, 1024-1034, 2020 | 187 | 2020 |
| Spectral bias and task-model alignment explain generalization in kernel regression and infinitely wide neural networks A Canatar, B Bordelon, C Pehlevan Nature communications 12 (1), 2914, 2021 | 171 | 2021 |
| The basal ganglia is necessary for learning spectral, but not temporal, features of birdsong F Ali, TM Otchy, C Pehlevan, AL Fantana, Y Burak, BP Ölveczky Neuron 80 (2), 494-506, 2013 | 149 | 2013 |
| A Hebbian/Anti-Hebbian Neural Network for Linear Subspace Learning: A Derivation from Multidimensional Scaling of Streaming Data C Pehlevan, T Hu, DB Chklovskii Neural computation 27 (7), 1461-1495, 2015 | 111 | 2015 |
| Why do similarity matching objectives lead to Hebbian/anti-Hebbian networks? C Pehlevan, AM Sengupta, DB Chklovskii Neural computation 30 (1), 84-124, 2017 | 77 | 2017 |
| Neural networks as kernel learners: The silent alignment effect A Atanasov, B Bordelon, C Pehlevan arXiv preprint arXiv:2111.00034, 2021 | 69 | 2021 |
| Internal state configures olfactory behavior and early sensory processing in Drosophila larvae K Vogt, DM Zimmerman, M Schlichting, L Hernandez-Nunez, S Qin, ... Science advances 7 (1), eabd6900, 2021 | 69 | 2021 |
| A normative theory of adaptive dimensionality reduction in neural networks C Pehlevan, D Chklovskii Advances in neural information processing systems 28, 2015 | 62 | 2015 |
| Neuroscience-inspired online unsupervised learning algorithms: Artificial neural networks C Pehlevan, DB Chklovskii IEEE Signal Processing Magazine 36 (6), 88-96, 2019 | 60 | 2019 |
| Complex Langevin equations and Schwinger–Dyson equations G Guralnik, C Pehlevan Nuclear Physics B 811 (3), 519-536, 2009 | 59 | 2009 |
| Self-consistent dynamical field theory of kernel evolution in wide neural networks B Bordelon, C Pehlevan Advances in Neural Information Processing Systems 35, 32240-32256, 2022 | 57 | 2022 |
| Exact marginal prior distributions of finite Bayesian neural networks J Zavatone-Veth, C Pehlevan Advances in Neural Information Processing Systems 34, 3364-3375, 2021 | 55* | 2021 |
| Selectivity and sparseness in randomly connected balanced networks C Pehlevan, H Sompolinsky PloS one 9 (2), e89992, 2014 | 50 | 2014 |
| A Hebbian/Anti-Hebbian Network Derived from Online Non-Negative Matrix Factorization Can Cluster and Discover Sparse Features C Pehlevan, DB Chklovskii Signals, Systems and Computers, 2014 48th Asilomar Conference on, 769-775, 2014 | 48 | 2014 |
| Asymptotics of representation learning in finite Bayesian neural networks J Zavatone-Veth, A Canatar, B Ruben, C Pehlevan Advances in neural information processing systems 34, 24765-24777, 2021 | 45 | 2021 |
| Manifold-tiling localized receptive fields are optimal in similarity-preserving neural networks A Sengupta, C Pehlevan, M Tepper, A Genkin, D Chklovskii Advances in neural information processing systems 31, 2018 | 41 | 2018 |
| Attention approximates sparse distributed memory T Bricken, C Pehlevan Advances in Neural Information Processing Systems 34, 15301-15315, 2021 | 38 | 2021 |
| Blind nonnegative source separation using biological neural networks C Pehlevan, S Mohan, DB Chklovskii Neural computation 29 (11), 2925-2954, 2017 | 38 | 2017 |
| Bandwidth enables generalization in quantum kernel models A Canatar, E Peters, C Pehlevan, SM Wild, R Shaydulin arXiv preprint arXiv:2206.06686, 2022 | 37 | 2022 |
Dmitri "Mitya" B. ChklovskiiFlatiron Institute, Simons Foundation and NYUVerified email at flatironinstitute.org
