239 citations · 1.1k across the 35 of their papers we have counts for
4 papers · 1 filter
Ridgeless Interpolation with Shallow ReLU Networks in is Nearest Neighbor Curvature Extrapolation and Provably Generalizes on Lipschitz Functions
Boris Hanin
We prove a precise geometric description of all one layer ReLU networks with a single linear unit and input/output dimensions equal to one that interpolate a given dataset…
Random Neural Networks in the Infinite Width Limit as Gaussian Processes
Boris Hanin
This article gives a new proof that fully connected neural networks with random weights and biases converge to Gaussian processes in the regime where the input dimension, output di…
The Principles of Deep Learning Theory
Daniel A. Roberts, Sho Yaida, Boris Hanin
This book develops an effective theory approach to understanding deep neural networks of practical relevance. Beginning from a first-principles component-level picture of networks,…
Deep ReLU Networks Preserve Expected Length
Boris Hanin, Ryan Jeong, David Rolnick
Assessing the complexity of functions computed by a neural network helps us understand how the network will learn and generalize. One natural measure of complexity is how the netwo…