Blake Bordelon

papers

494

total citations

papers (12)

Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

NEURIPS 2022arXiv

116

citations

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit

ICLR 2024arXiv

citations

Feature-Learning Networks Are Consistent Across Widths At Realistic Scales

NEURIPS 2023arXiv

citations

Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks

NEURIPS 2023arXiv

citations

Out-of-Distribution Generalization in Kernel Regression

NEURIPS 2021arXiv

citations

Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer

ICML 2025arXiv

citations

A Model of Place Field Reorganization During Reward Maximization

ICML 2025

citations

Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex

ICLR 2025

citations

Loss Dynamics of Temporal Difference Reinforcement Learning

NEURIPS 2023arXiv

citations

Blake Bordelon

papers (12)

Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

A Dynamical Model of Neural Scaling Laws

Grokking as the transition from lazy to rich training dynamics

Scaling Laws for Precision

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit

Feature-Learning Networks Are Consistent Across Widths At Realistic Scales

Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks

Out-of-Distribution Generalization in Kernel Regression

Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer

A Model of Place Field Reorganization During Reward Maximization

Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex

Loss Dynamics of Temporal Difference Reinforcement Learning

papers (12)

Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

A Dynamical Model of Neural Scaling Laws

Grokking as the transition from lazy to rich training dynamics

Scaling Laws for Precision

Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit

Feature-Learning Networks Are Consistent Across Widths At Realistic Scales

Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks

Out-of-Distribution Generalization in Kernel Regression

Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer

A Model of Place Field Reorganization During Reward Maximization

Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex

Loss Dynamics of Temporal Difference Reinforcement Learning