3 papers
cs.CL2025
Pretraining Large Language Models with NVFP4
NVIDIA, Felix Abecassis, Anjulie Agrusa +87
Large Language Models (LLMs) today are powerful problem solvers across many domains, and they continue to get stronger as they scale in model size, training set size, and training…
cs.LG2025
The Spectral Bias of Shallow Neural Network Learning is Shaped by the Choice of Non-linearity
Justin Sahs, Ryan Pyle, Fabio Anselmi +1
Despite classical statistical theory predicting severe overfitting, modern massively overparameterized neural networks still generalize well. This unexpected property is attributed…
cs.LG2023
A Quantitative Approach to Predicting Representational Learning and Performance in Neural Networks
Ryan Pyle, Sebastian Musslick, Jonathan D. Cohen +1
A key property of neural networks (both biological and artificial) is how they learn to represent and manipulate input information in order to solve a task. Different types of repr…