Publications

2024
B. Bordelon, A. Atanasov, and C. Pehlevan, “A Dynamical Model of Neural Scaling Laws ,” arXiv:2402.01092, 2024.
T. Kumar, B. Bordelon, S. J. Gershman, and C. Pehlevan, “Grokking as the Transition from Lazy to Rich Training Dynamics,” International Conference on Learning Representations (ICLR), 2024. PDF
B. Bordelon*, L. Noci*, M. B. Li, B. Hanin*, and C. Pehlevan*, “Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit,” International Conference on Learning Representations (ICLR), 2024. PDF
2023
B. Bordelon*, L. Noci*, M. Li, B. Hanin*, and C. Pehlevan*, “Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit,” in NeurIPS 2023 Workshop on Mathematics of Modern Machine Learning, 2023. PDF
H. T. Chaudhry, J. A. Zavatone-Veth, D. Krotov, and C. Pehlevan, “Long Sequence Hopfield Memory,” in Associative Memory & Hopfield Networks in 2023 Workshop, NeurIPS, 2023. PDF
N. M. Chapochnikov, C. Pehlevan, and D. B. Chklovskii, “Reply to Castro et al.: Do connectomes possess markers of activity-dependent synaptic plasticity?Proceedings of the National Academy of Sciences (PNAS), vol. 120, no. 50, pp. e2317056120, 2023. PDF
B. Bordelon and C. Pehlevan, “Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks,” Journal of Statistical Mechanics: Theory and Experiment (Machine Learning Special Issue), pp. 114009, 2023. PDF
B. Bordelon, P. Masset, H. Kuo, and C. Pehlevan, “Loss Dynamics of Temporal Difference Reinforcement Learning ,” in Advances in Neural Information Processing Systems (NeurIPS), 2023. PDF
N. M. Chapochnikov, C. Pehlevan, and D. B. Chklovskii, “Normative and mechanistic model of an adaptive circuit for efficient encoding and feature extraction,” Proceedings of the National Academy of Sciences (PNAS), vol. 120, no. 29, pp. e2117484120, 2023. PDF
B. S. Ruben and C. Pehlevan, “Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles,” in Advances in Neural Information Processing Systems (NeurIPS), 2023. PDF
J. A. Zavatone-Veth*, P. Masset*, W. L. Tong, J. D. Zak, V. N. Murthy*, and C. Pehlevan*, “Neural circuits for fast Poisson compressed sensing in the olfactory bulb,” in Advances in Neural Information Processing Systems (NeurIPS), 2023. PDF
B. Bozkurt, C. Pehlevan, and A. Erdogan, “Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks without Weight Symmetry,” Advances in Neural Information Processing Systems (NeurIPS), 2023. PDF
M. Farrell and C. Pehlevan, “Recall tempo of Hebbian sequences depends on the interplay of Hebbian kernel with tutor signal timing,” biorXiv, 2023.
H. T. Chaudhry, J. A. Zavatone-Veth, D. Krotov, and C. Pehlevan, “Long Sequence Hopfield Memory,” in Advances in Neural Information Processing Systems (NeurIPS), 2023. PDF
N. Vyas*, A. Atanasov*, B. Bordelon*, D. Morwani, S. Sainathan, and C. Pehlevan, “Feature-Learning Networks Are Consistent Across Widths At Realistic Scales,” Advances in Neural Information Processing Systems (NeurIPS), 2023. PDF
B. Bordelon and C. Pehlevan, “Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks,” Advances in Neural Information Processing Systems (NeurIPS) (Spotlight), 2023. PDF
J. A. Zavatone-Veth and C. Pehlevan, “Learning curves for deep structured Gaussian feature models,” in Advances in Neural Information Processing Systems (NeurIPS), 2023. PDF
J. A. Zavatone-Veth, S. Yang*, J. A. Rubinfien*, and C. Pehlevan, “Neural networks learn to magnify areas near decision boundaries,” arXiv preprint arXiv:2301.11375, 2023.
A. Atanasov*, B. Bordelon*, S. Sainathan, and C. Pehlevan, “The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes,” International Conference on Learning Representations (ICLR), 2023. PDF
S. Qin, S. Farashahi*, D. Lipshutz*, A. Sengupta, D. B. Chklovskii, and C. Pehlevan, “Coordinated drift of receptive fields in Hebbian/anti-Hebbian network models during noisy representation learning,” Nature Neuroscience , vol. 26, pp. 339–349, 2023. PDF

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