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Cengiz Pehlevan
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Publications
- 2024
- [i47]Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan:
A Dynamical Model of Neural Scaling Laws. CoRR abs/2402.01092 (2024) - 2023
- [c43]Alexander Atanasov, Blake Bordelon, Sabarish Sainathan, Cengiz Pehlevan:
The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes. ICLR 2023 - [c42]Blake Bordelon, Cengiz Pehlevan:
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks. ICLR 2023 - [c39]Nikhil Vyas, Alexander Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan:
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales. NeurIPS 2023 - [c38]Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan:
Loss Dynamics of Temporal Difference Reinforcement Learning. NeurIPS 2023 - [c37]Blake Bordelon, Cengiz Pehlevan:
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks. NeurIPS 2023 - [c35]Hamza Tahir Chaudhry, Jacob A. Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan:
Long Sequence Hopfield Memory. NeurIPS 2023 - [c34]Benjamin S. Ruben, Cengiz Pehlevan:
Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles. NeurIPS 2023 - [c33]Jacob A. Zavatone-Veth, Paul Masset, William L. Tong, Joseph D. Zak, Venkatesh Murthy, Cengiz Pehlevan:
Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb. NeurIPS 2023 - [c32]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Learning Curves for Deep Structured Gaussian Feature Models. NeurIPS 2023 - [i46]Jacob A. Zavatone-Veth, Sheng Yang, Julian A. Rubinfien, Cengiz Pehlevan:
Neural networks learn to magnify areas near decision boundaries. CoRR abs/2301.11375 (2023) - [i45]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Learning curves for deep structured Gaussian feature models. CoRR abs/2303.00564 (2023) - [i44]Blake Bordelon, Cengiz Pehlevan:
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks. CoRR abs/2304.03408 (2023) - [i43]Nikhil Vyas, Alexander Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan:
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales. CoRR abs/2305.18411 (2023) - [i42]Hamza Tahir Chaudhry, Jacob A. Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan:
Long Sequence Hopfield Memory. CoRR abs/2306.04532 (2023) - [i40]Benjamin S. Ruben, Cengiz Pehlevan:
Learning Curves for Heterogeneous Feature-Subsampled Ridge Ensembles. CoRR abs/2307.03176 (2023) - [i39]Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan:
Dynamics of Temporal Difference Reinforcement Learning. CoRR abs/2307.04841 (2023) - [i38]Blake Bordelon, Lorenzo Noci, Mufan Bill Li, Boris Hanin, Cengiz Pehlevan:
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit. CoRR abs/2309.16620 (2023) - [i37]Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan:
Grokking as the Transition from Lazy to Rich Training Dynamics. CoRR abs/2310.06110 (2023) - 2022
- [j7]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
On Neural Network Kernels and the Storage Capacity Problem. Neural Comput. 34(5): 1136-1142 (2022) - [c31]Abdulkadir Canatar, Cengiz Pehlevan:
A Kernel Analysis of Feature Learning in Deep Neural Networks. Allerton 2022: 1-8 - [c30]Alexander Atanasov, Blake Bordelon, Cengiz Pehlevan:
Neural Networks as Kernel Learners: The Silent Alignment Effect. ICLR 2022 - [c29]Blake Bordelon, Cengiz Pehlevan:
Learning Curves for SGD on Structured Features. ICLR 2022 - [c28]Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan:
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? ICLR 2022 - [c27]Blake Bordelon, Cengiz Pehlevan:
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks. NeurIPS 2022 - [c25]Paul Masset, Jacob A. Zavatone-Veth, J. Patrick Connor, Venkatesh Murthy, Cengiz Pehlevan:
Natural gradient enables fast sampling in spiking neural networks. NeurIPS 2022 - [i36]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
On neural network kernels and the storage capacity problem. CoRR abs/2201.04669 (2022) - [i35]Jacob A. Zavatone-Veth, William L. Tong, Cengiz Pehlevan:
Contrasting random and learned features in deep Bayesian linear regression. CoRR abs/2203.00573 (2022) - [i34]Blake Bordelon, Cengiz Pehlevan:
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks. CoRR abs/2205.09653 (2022) - [i33]Abdulkadir Canatar, Evan Peters, Cengiz Pehlevan, Stefan M. Wild, Ruslan Shaydulin:
Bandwidth Enables Generalization in Quantum Kernel Models. CoRR abs/2206.06686 (2022) - [i30]Blake Bordelon, Cengiz Pehlevan:
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks. CoRR abs/2210.02157 (2022) - [i28]Alexander Atanasov, Blake Bordelon, Sabarish Sainathan, Cengiz Pehlevan:
The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes. CoRR abs/2212.12147 (2022) - 2021
- [j6]Shanshan Qin, Nayantara Mudur, Cengiz Pehlevan:
Contrastive Similarity Matching for Supervised Learning. Neural Comput. 33(5): 1300-1328 (2021) - [c24]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Depth induces scale-averaging in overparameterized linear Bayesian neural networks. ACSCC 2021: 600-607 - [c23]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Exact marginal prior distributions of finite Bayesian neural networks. NeurIPS 2021: 3364-3375 - [c22]Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan:
Out-of-Distribution Generalization in Kernel Regression. NeurIPS 2021: 12600-12612 - [c21]Trenton Bricken, Cengiz Pehlevan:
Attention Approximates Sparse Distributed Memory. NeurIPS 2021: 15301-15315 - [c20]Jacob A. Zavatone-Veth, Abdulkadir Canatar, Benjamin S. Ruben, Cengiz Pehlevan:
Asymptotics of representation learning in finite Bayesian neural networks. NeurIPS 2021: 24765-24777 - [i27]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Exact priors of finite neural networks. CoRR abs/2104.11734 (2021) - [i26]Jacob A. Zavatone-Veth, Abdulkadir Canatar, Cengiz Pehlevan:
Asymptotics of representation learning in finite Bayesian neural networks. CoRR abs/2106.00651 (2021) - [i25]Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan:
Out-of-Distribution Generalization in Kernel Regression. CoRR abs/2106.02261 (2021) - [i24]Blake Bordelon, Cengiz Pehlevan:
Learning Curves for SGD on Structured Features. CoRR abs/2106.02713 (2021) - [i23]Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan:
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views? CoRR abs/2110.07472 (2021) - [i22]Alexander Atanasov, Blake Bordelon, Cengiz Pehlevan:
Neural Networks as Kernel Learners: The Silent Alignment Effect. CoRR abs/2111.00034 (2021) - [i21]Trenton Bricken, Cengiz Pehlevan:
Attention Approximates Sparse Distributed Memory. CoRR abs/2111.05498 (2021) - [i20]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Depth induces scale-averaging in overparameterized linear Bayesian neural networks. CoRR abs/2111.11954 (2021) - 2020
- [c18]Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan:
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks. ICML 2020: 1024-1034 - [c16]Qianyi Li, Cengiz Pehlevan:
Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons. NeurIPS 2020 - [i19]Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan:
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks. CoRR abs/2002.02561 (2020) - [i18]Shanshan Qin, Nayantara Mudur, Cengiz Pehlevan:
Supervised Deep Similarity Matching. CoRR abs/2002.10378 (2020) - [i16]Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan:
Statistical Mechanics of Generalization in Kernel Regression. CoRR abs/2006.13198 (2020) - [i14]Jacob A. Zavatone-Veth, Cengiz Pehlevan:
Activation function dependence of the storage capacity of treelike neural networks. CoRR abs/2007.11136 (2020)
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last updated on 2024-03-03 02:39 CET by the dblp team
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