Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach

2 May 2018

Papers citing "Trainability and Accuracy of Neural Networks: An Interacting Particle System Approach"

20 / 20 papers shown

Title
Function-Space Learning Rates Edward Milsom Ben Anson Laurence Aitchison 88 1 0 24 Feb 2025
Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer Blake Bordelon Cengiz Pehlevan AI4CE 124 1 0 04 Feb 2025
Mean-Field Analysis for Learning Subspace-Sparse Polynomials with Gaussian Input Ziang Chen Rong Ge MLT 99 1 0 10 Jan 2025
Emergence of meta-stable clustering in mean-field transformer models Giuseppe Bruno Federico Pasqualotto Andrea Agazzi 58 8 0 30 Oct 2024
Optimal Protocols for Continual Learning via Statistical Physics and Control Theory Francesco Mori Stefano Sarao Mannelli Francesca Mignacco 101 3 0 26 Sep 2024
From Lazy to Rich: Exact Learning Dynamics in Deep Linear Networks Clémentine Dominé Nicolas Anguita A. Proca Lukas Braun D. Kunin P. Mediano Andrew M. Saxe 72 3 0 22 Sep 2024
Symmetries in Overparametrized Neural Networks: A Mean-Field View Javier Maass Joaquin Fontbona MLT FedML 66 2 0 30 May 2024
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions Luca Arnaboldi Yatin Dandi Florent Krzakala Luca Pesce Ludovic Stephan 86 14 0 24 May 2024
Stochastic Modified Equations and Dynamics of Stochastic Gradient Algorithms I: Mathematical Foundations Qianxiao Li Cheng Tai E. Weinan 90 149 0 05 Nov 2018
On the Global Convergence of Gradient Descent for Over-parameterized Models using Optimal Transport Lénaïc Chizat Francis R. Bach OT 157 731 0 24 May 2018
A Mean Field View of the Landscape of Two-Layers Neural Networks Song Mei Andrea Montanari Phan-Minh Nguyen MLT 76 855 0 18 Apr 2018
Comparing Dynamics: Deep Neural Networks versus Glassy Systems Marco Baity-Jesi Levent Sagun Mario Geiger S. Spigler Gerard Ben Arous C. Cammarota Yann LeCun Matthieu Wyart Giulio Biroli AI4CE 87 113 0 19 Mar 2018
Solving for high dimensional committor functions using artificial neural networks Y. Khoo Jianfeng Lu Lexing Ying 51 137 0 28 Feb 2018
A unified deep artificial neural network approach to partial differential equations in complex geometries Jens Berg K. Nystrom AI4CE 50 583 0 17 Nov 2017
Machine learning approximation algorithms for high-dimensional fully nonlinear partial differential equations and second-order backward stochastic differential equations C. Beck Weinan E Arnulf Jentzen 43 329 0 18 Sep 2017
Deep learning-based numerical methods for high-dimensional parabolic partial differential equations and backward stochastic differential equations Weinan E Jiequn Han Arnulf Jentzen 107 790 0 15 Jun 2017
Stochastic modified equations and adaptive stochastic gradient algorithms Qianxiao Li Cheng Tai E. Weinan 54 282 0 19 Nov 2015
Breaking the Curse of Dimensionality with Convex Neural Networks Francis R. Bach 118 703 0 30 Dec 2014
Explorations on high dimensional landscapes Levent Sagun V. U. Güney Gerard Ben Arous Yann LeCun 47 65 0 20 Dec 2014
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 230 1,191 0 30 Nov 2014