Blake Bordelon
22 papers · 2020–2025 · 4 venues · across top CS/AI venues
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(11)
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(84)
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(2)
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Venues
Top co-authors
Research topics
Machine Learning
(21)
Optimization & Theory Β· Machine Learning
(21)
Deep Learning
(11)
Architectures
(11)
Core Methods
(6)
Application Areas
(4)
Optimization & Theory Β· Deep Learning
(2)
Artificial Intelligence
(1)
Mathematics & Optimization
(1)
Reinforcement Learning
(1)
Robotics
(1)
Applications
(1)
Capabilities
(1)
Core AI
(1)
Methods
(1)
Keywords
feature learning
(7)
neural tangent kernel
(7)
representation learning
(5)
gradient descent
(4)
dynamical mean field theory
(3)
kernel methods
(3)
neural network optimization
(3)
kernel regression
(3)
infinite-width neural network
(2)
infinite-width limit
(2)
neural network
(2)
lazy training
(2)
scaling law
(2)
hyperparameter transfer
(2)
learning dynamics
(2)
residual network
(2)
gradient flow
(2)
generalization error
(2)
learning curve
(2)
variance analysis
(2)
Papers
Adaptive kernel predictors from feature-learning infinite limits of neural networks
ICML 2025
A Model of Place Field Reorganization During Reward Maximization
ICML 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
ICML 2025
Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex
ICLR 2025
How Feature Learning Can Improve Neural Scaling Laws
ICLR 2025
Scaling Laws for Precision
ICLR 2025
A Dynamical Model of Neural Scaling Laws
ICML 2024
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
ICLR 2024
Grokking as the transition from lazy to rich training dynamics
ICLR 2024
Infinite Limits of Multi-head Transformer Dynamics
NeurIPS 2024
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
NeurIPS 2023
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales
NeurIPS 2023
Loss Dynamics of Temporal Difference Reinforcement Learning
NeurIPS 2023
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks
ICLR 2023
The Onset of Variance-Limited Behavior for Networks in the Lazy and Rich Regimes
ICLR 2023
Capacity of Group-invariant Linear Readouts from Equivariant Representations: How Many Objects can be Linearly Classified Under All Possible Views?
ICLR 2022
Learning Curves for SGD on Structured Features
ICLR 2022
Neural Networks as Kernel Learners: The Silent Alignment Effect
ICLR 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
NeurIPS 2022
Efficient online inference for nonparametric mixture models
UAI 2021
Out-of-Distribution Generalization in Kernel Regression
NeurIPS 2021
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
ICML 2020