Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models

16 October 2023

Papers citing "Wide Neural Networks as Gaussian Processes: Lessons from Deep Equilibrium Models"

5 / 5 papers shown

Title
Allocating Variance to Maximize Expectation R. Leme Cliff Stein Yifeng Teng Pratik Worah 73 0 0 25 Feb 2025
Global Convergence Rate of Deep Equilibrium Models with General Activations Lan V. Truong 39 2 0 11 Feb 2023
Gradient Descent Optimizes Infinite-Depth ReLU Implicit Networks with Linear Widths Tianxiang Gao Hongyang Gao MLT 35 5 0 16 May 2022
On the Proof of Global Convergence of Gradient Descent for Deep ReLU Networks with Linear Widths Quynh N. Nguyen 41 48 0 24 Jan 2021
Stable ResNet Soufiane Hayou Eugenio Clerico Bo He George Deligiannidis Arnaud Doucet Judith Rousseau ODL SSeg 46 51 0 24 Oct 2020