Pehlevan, Cengiz

59 publications

ICML 2025 A Model of Place Field Reorganization During Reward Maximization M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth, Cengiz Pehlevan

NeurIPS 2025 A Solvable Model of Learning Generative Diffusion: Theory and Insights Hugo Cui, Cengiz Pehlevan, Yue M. Lu

ICML 2025 Adaptive Kernel Predictors from Feature-Learning Infinite Limits of Neural Networks Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan

NeurIPS 2025 An Analytical Theory of Spectral Bias in the Learning Dynamics of Diffusion Models Binxu Wang, Cengiz Pehlevan

TMLR 2025 Convex Relaxation for Solving Large-Margin Classifiers in Hyperbolic Space Sheng Yang, Peihan Liu, Cengiz Pehlevan

ICML 2025 Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer Blake Bordelon, Cengiz Pehlevan

ICLR 2025 Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex Tanishq Kumar, Blake Bordelon, Cengiz Pehlevan, Venkatesh N Murthy, Samuel J. Gershman

NeurIPS 2025 Don't Be Lazy: CompleteP Enables Compute-Efficient Deep Transformers Nolan Simran Dey, Bin Claire Zhang, Lorenzo Noci, Mufan Li, Blake Bordelon, Shane Bergsma, Cengiz Pehlevan, Boris Hanin, Joel Hestness

NeurIPS 2025 Error Broadcast and Decorrelation as a Potential Artificial and Natural Learning Mechanism Mete Erdogan, Cengiz Pehlevan, Alper Tunga Erdogan

ICLR 2025 How Feature Learning Can Improve Neural Scaling Laws Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan

ICLR 2025 MLPs Learn In-Context on Regression and Classification Tasks William Lingxiao Tong, Cengiz Pehlevan

ICML 2025 No Free Lunch from Random Feature Ensembles: Scaling Laws and Near-Optimality Conditions Benjamin Samuel Ruben, William Lingxiao Tong, Hamza Tahir Chaudhry, Cengiz Pehlevan

ICLRW 2025 Place Field Representation Learning During Policy Learning M Ganesh Kumar, Blake Bordelon, Jacob A Zavatone-Veth, Cengiz Pehlevan

ICML 2025 Risk and Cross Validation in Ridge Regression with Correlated Samples Alexander Atanasov, Jacob A Zavatone-Veth, Cengiz Pehlevan

ICLR 2025 Scaling Laws for Precision Tanishq Kumar, Zachary Ankner, Benjamin Frederick Spector, Blake Bordelon, Niklas Muennighoff, Mansheej Paul, Cengiz Pehlevan, Christopher Re, Aditi Raghunathan

ICLRW 2025 Test-Time Scaling Meets Associative Memory: Challenges in Subquadratic Models Hamza Tahir Chaudhry, Mohit Kulkarni, Cengiz Pehlevan

ICLR 2025 The Optimization Landscape of SGD Across the Feature Learning Strength Alexander Atanasov, Alexandru Meterez, James B Simon, Cengiz Pehlevan

ICML 2024 A Dynamical Model of Neural Scaling Laws Blake Bordelon, Alexander Atanasov, Cengiz Pehlevan

NeurIPSW 2024 Adversarially-Robust Representation Learning Through Spectral Regularization of Features Sheng Yang, Jacob A Zavatone-Veth, Cengiz Pehlevan

ICMLW 2024 Asymptotic Dynamics for Delayed Feature Learning in a Toy Model Blake Bordelon, Tanishq Kumar, Samuel J. Gershman, Cengiz Pehlevan

ICLR 2024 Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit Blake Bordelon, Lorenzo Noci, Mufan Bill Li, Boris Hanin, Cengiz Pehlevan

ICLR 2024 Grokking as the Transition from Lazy to Rich Training Dynamics Tanishq Kumar, Blake Bordelon, Samuel J. Gershman, Cengiz Pehlevan

NeurIPSW 2024 In-Context Learning by Linear Attention: Exact Asymptotics and Experiments Yue Lu, Mary Letey, Jacob A Zavatone-Veth, Anindita Maiti, Cengiz Pehlevan

NeurIPS 2024 Infinite Limits of Multi-Head Transformer Dynamics Blake Bordelon, Hamza Chaudhry, Cengiz Pehlevan

NeurIPS 2024 Partial Observation Can Induce Mechanistic Mismatches in Data-Constrained Models of Neural Dynamics William Qian, Jacob A. Zavatone-Veth, Benjamin S. Ruben, Cengiz Pehlevan

NeurIPSW 2024 Partial Observation Can Induce Mechanistic Mismatches in Data-Constrained RNNs William Qian, Jacob A Zavatone-Veth, Benjamin Samuel Ruben, Cengiz Pehlevan

TMLR 2023 Bandwidth Enables Generalization in Quantum Kernel Models Abdulkadir Canatar, Evan Peters, Cengiz Pehlevan, Stefan M. Wild, Ruslan Shaydulin

ICLR 2023 Correlative Information Maximization Based Biologically Plausible Neural Networks for Correlated Source Separation Bariscan Bozkurt, Ateş İsfendiyaroğlu, Cengiz Pehlevan, Alper Tunga Erdogan

NeurIPS 2023 Correlative Information Maximization: A Biologically Plausible Approach to Supervised Deep Neural Networks Without Weight Symmetry Bariscan Bozkurt, Cengiz Pehlevan, Alper Erdogan

NeurIPSW 2023 Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit Blake Bordelon, Lorenzo Noci, Mufan Li, Boris Hanin, Cengiz Pehlevan

NeurIPS 2023 Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks Blake Bordelon, Cengiz Pehlevan

NeurIPS 2023 Feature-Learning Networks Are Consistent Across Widths at Realistic Scales Nikhil Vyas, Alexander Atanasov, Blake Bordelon, Depen Morwani, Sabarish Sainathan, Cengiz Pehlevan

ICLR 2023 Interneurons Accelerate Learning Dynamics in Recurrent Neural Networks for Statistical Adaptation David Lipshutz, Cengiz Pehlevan, Dmitri Chklovskii

NeurIPS 2023 Learning Curves for Deep Structured Gaussian Feature Models Jacob Zavatone-Veth, Cengiz Pehlevan

NeurIPS 2023 Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles Ben Ruben, Cengiz Pehlevan

NeurIPS 2023 Long Sequence Hopfield Memory Hamza Chaudhry, Jacob Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan

NeurIPSW 2023 Long Sequence Hopfield Memory Hamza Tahir Chaudhry, Jacob A Zavatone-Veth, Dmitry Krotov, Cengiz Pehlevan

NeurIPS 2023 Loss Dynamics of Temporal Difference Reinforcement Learning Blake Bordelon, Paul Masset, Henry Kuo, Cengiz Pehlevan

NeurIPS 2023 Neural Circuits for Fast Poisson Compressed Sensing in the Olfactory Bulb Jacob Zavatone-Veth, Paul Masset, William Tong, Joseph D. Zak, Venkatesh Murthy, Cengiz Pehlevan

ICLR 2023 The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks Blake Bordelon, Cengiz Pehlevan

ICLR 2023 The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes Alexander Atanasov, Blake Bordelon, Sabarish Sainathan, Cengiz Pehlevan

NeurIPS 2022 Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated Sources Bariscan Bozkurt, Cengiz Pehlevan, Alper Erdogan

ICLR 2022 Capacity of Group-Invariant Linear Readouts from Equivariant Representations: How Many Objects Can Be Linearly Classified Under All Possible Views? Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan

NeurIPSW 2022 Capacity of Group-Invariant Linear Readouts from Equivariant Representations: How Many Objects Can Be Linearly Classified Under All Possible Views? Matthew Farrell, Blake Bordelon, Shubhendu Trivedi, Cengiz Pehlevan

ICLR 2022 Learning Curves for SGD on Structured Features Blake Bordelon, Cengiz Pehlevan

NeurIPS 2022 Natural Gradient Enables Fast Sampling in Spiking Neural Networks Paul Masset, Jacob Zavatone-Veth, J. Patrick Connor, Venkatesh Murthy, Cengiz Pehlevan

ICLR 2022 Neural Networks as Kernel Learners: The Silent Alignment Effect Alexander Atanasov, Blake Bordelon, Cengiz Pehlevan

NeurIPS 2022 Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks Blake Bordelon, Cengiz Pehlevan

NeurIPSW 2022 Training Shapes the Curvature of Shallow Neural Network Representations Jacob A Zavatone-Veth, Julian Alex Rubinfien, Cengiz Pehlevan

NeurIPS 2021 Asymptotics of Representation Learning in Finite Bayesian Neural Networks Jacob Zavatone-Veth, Abdulkadir Canatar, Ben Ruben, Cengiz Pehlevan

NeurIPS 2021 Attention Approximates Sparse Distributed Memory Trenton Bricken, Cengiz Pehlevan

NeurIPS 2021 Exact Marginal Prior Distributions of Finite Bayesian Neural Networks Jacob Zavatone-Veth, Cengiz Pehlevan

NeurIPS 2021 Out-of-Distribution Generalization in Kernel Regression Abdulkadir Canatar, Blake Bordelon, Cengiz Pehlevan

ICML 2020 Associative Memory in Iterated Overparameterized Sigmoid Autoencoders Yibo Jiang, Cengiz Pehlevan

NeurIPS 2020 Minimax Dynamics of Optimally Balanced Spiking Networks of Excitatory and Inhibitory Neurons Qianyi Li, Cengiz Pehlevan

ICML 2020 Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks Blake Bordelon, Abdulkadir Canatar, Cengiz Pehlevan

NeurIPS 2019 Structured and Deep Similarity Matching via Structured and Deep Hebbian Networks Dina Obeid, Hugo Ramambason, Cengiz Pehlevan

NeurIPS 2018 Manifold-Tiling Localized Receptive Fields Are Optimal in Similarity-Preserving Neural Networks Anirvan Sengupta, Cengiz Pehlevan, Mariano Tepper, Alexander Genkin, Dmitri Chklovskii

NeurIPS 2015 A Normative Theory of Adaptive Dimensionality Reduction in Neural Networks Cengiz Pehlevan, Dmitri Chklovskii