Deep Relaxation: partial differential equations for optimizing deep neural networks

17 April 2017

Stanley Osher

Papers citing "Deep Relaxation: partial differential equations for optimizing deep neural networks"

21 / 21 papers shown

Title
Stochastic Optimal Control for Diffusion Bridges in Function Spaces Byoungwoo Park Jungwon Choi Sungbin Lim Juho Lee 50 3 0 31 May 2024
Stochastic Optimal Control Matching Carles Domingo-Enrich Jiequn Han Brandon Amos Joan Bruna Ricky T. Q. Chen DiffM 18 6 0 04 Dec 2023
Learning Rate Schedules in the Presence of Distribution Shift Matthew Fahrbach Adel Javanmard Vahab Mirrokni Pratik Worah 19 6 0 27 Mar 2023
On Large Batch Training and Sharp Minima: A Fokker-Planck Perspective Xiaowu Dai Yuhua Zhu 14 4 0 02 Dec 2021
Quantized Convolutional Neural Networks Through the Lens of Partial Differential Equations Ido Ben-Yair Gil Ben Shalom Moshe Eliasof Eran Treister MQ 16 5 0 31 Aug 2021
Cell-average based neural network method for hyperbolic and parabolic partial differential equations Changxin Qiu Jue Yan 14 10 0 02 Jul 2021
dNNsolve: an efficient NN-based PDE solver V. Guidetti F. Muia Y. Welling A. Westphal 25 6 0 15 Mar 2021
On Bayesian posterior mean estimators in imaging sciences and Hamilton-Jacobi Partial Differential Equations Jérome Darbon G. P. Langlois 16 8 0 12 Mar 2020
Neural ODEs as the Deep Limit of ResNets with constant weights B. Avelin K. Nystrom ODL 32 31 0 28 Jun 2019
Maximum Mean Discrepancy Gradient Flow Michael Arbel Anna Korba Adil Salim A. Gretton 24 158 0 11 Jun 2019
Towards Theoretical Understanding of Large Batch Training in Stochastic Gradient Descent Xiaowu Dai Yuhua Zhu 17 11 0 03 Dec 2018
Laplacian Smoothing Gradient Descent Stanley Osher Bao Wang Penghang Yin Xiyang Luo Farzin Barekat Minh Pham A. Lin ODL 14 43 0 17 Jun 2018
Deep Neural Networks Motivated by Partial Differential Equations Lars Ruthotto E. Haber AI4CE 25 483 0 12 Apr 2018
BinaryRelax: A Relaxation Approach For Training Deep Neural Networks With Quantized Weights Penghang Yin Shuai Zhang J. Lyu Stanley Osher Y. Qi Jack Xin MQ 22 78 0 19 Jan 2018
A short variational proof of equivalence between policy gradients and soft Q learning Pierre Harvey Richemond B. Maginnis 6 5 0 22 Dec 2017
Convergent Block Coordinate Descent for Training Tikhonov Regularized Deep Neural Networks Ziming Zhang M. Brand 21 70 0 20 Nov 2017
A unified deep artificial neural network approach to partial differential equations in complex geometries Jens Berg K. Nystrom AI4CE 22 578 0 17 Nov 2017
Stochastic Backward Euler: An Implicit Gradient Descent Algorithm for $k$ -means Clustering Penghang Yin Minh Pham Adam M. Oberman Stanley Osher FedML 32 15 0 21 Oct 2017
Proximal Backpropagation Thomas Frerix Thomas Möllenhoff Michael Möller Daniel Cremers 13 31 0 14 Jun 2017
The Loss Surfaces of Multilayer Networks A. Choromańska Mikael Henaff Michaël Mathieu Gerard Ben Arous Yann LeCun ODL 179 1,185 0 30 Nov 2014
MCMC using Hamiltonian dynamics Radford M. Neal 185 3,262 0 09 Jun 2012