Blake Bordelon
22 papers · 2020–2025 · 4 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (4) 🏃 Academic Marathon (5) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🐝 Cross-Pollinator (6)
🧭
Keyword Pioneer
🤝
Dynamic Duo
(21)
👑
Triple Crown
💎
Century Club
(22)
🔥
Unstoppable
(6)
⚡
Prolific Year
(5)
❓
The Questioner
(2)
Conferences
ICLR (10)
NIPS (6)
ICML (5)
UAI (1)
Top co-authors
Keywords
neural tangent kernel
(3)
feature learning
(3)
neural network optimization
(3)
kernel regression
(2)
infinite width limit
(2)
kernel methods
(2)
dynamical mean field theory
(2)
out-of-distribution generalization
(1)
mean field theory
(1)
representation learning
(1)
network dynamics
(1)
hyperparameter transfer
(1)
function approximation
(1)
markov chain monte carlo
(1)
temporal difference learning
(1)
generalization error
(1)
value function
(1)
variational inference
(1)
gaussian process
(1)
markov decision process
(1)
Papers
A Model of Place Field Reorganization During Reward Maximization
ICML 2025
Scaling Laws for Precision
ICLR 2025
Do Mice Grok? Glimpses of Hidden Progress in Sensory Cortex
ICLR 2025
How Feature Learning Can Improve Neural Scaling Laws
ICLR 2025
Adaptive kernel predictors from feature-learning infinite limits of neural networks
ICML 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer
ICML 2025
Infinite Limits of Multi-head Transformer Dynamics
NIPS 2024
Grokking as the transition from lazy to rich training dynamics
ICLR 2024
Depthwise Hyperparameter Transfer in Residual Networks: Dynamics and Scaling Limit
ICLR 2024
A Dynamical Model of Neural Scaling Laws
ICML 2024
The Influence of Learning Rule on Representation Dynamics in Wide Neural Networks
ICLR 2023
Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
NIPS 2023
Loss Dynamics of Temporal Difference Reinforcement Learning
NIPS 2023
Feature-Learning Networks Are Consistent Across Widths At Realistic Scales
NIPS 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
Neural Networks as Kernel Learners: The Silent Alignment Effect
ICLR 2022
Learning Curves for SGD on Structured Features
ICLR 2022
Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks
NIPS 2022
Efficient online inference for nonparametric mixture models
UAI 2021
Out-of-Distribution Generalization in Kernel Regression
NIPS 2021
Spectrum Dependent Learning Curves in Kernel Regression and Wide Neural Networks
ICML 2020