Globally Convergent Multilevel Training of Deep Residual Networks

15 July 2021

Papers citing "Globally Convergent Multilevel Training of Deep Residual Networks"

9 / 9 papers shown

Title
A multilevel approach to accelerate the training of Transformers Guillaume Lauga Maël Chaumette Edgar Desainte-Maréville Étienne Lasalle Arthur Lebeurrier AI4CE 34 0 0 24 Apr 2025
Two-level overlapping additive Schwarz preconditioner for training scientific machine learning applications Youngkyu Lee Alena Kopanicáková George Karniadakis AI4CE 38 0 0 16 Jun 2024
Parallel Trust-Region Approaches in Neural Network Training: Beyond Traditional Methods Ken Trotti Samuel A. Cruz Alegría Alena Kopanicáková Rolf Krause 21 0 0 21 Dec 2023
Enhancing training of physics-informed neural networks using domain-decomposition based preconditioning strategies Alena Kopanicáková Hardik Kothari George Karniadakis Rolf Krause AI4CE 27 18 0 30 Jun 2023
A Block-Coordinate Approach of Multi-level Optimization with an Application to Physics-Informed Neural Networks Serge Gratton Valentin Mercier E. Riccietti P. Toint AI4CE 28 5 0 23 May 2023
Multilevel Objective-Function-Free Optimization with an Application to Neural Networks Training Serge Gratton Alena Kopanicáková P. Toint 6 7 0 14 Feb 2023
A Domain Decomposition-Based CNN-DNN Architecture for Model Parallel Training Applied to Image Recognition Problems A. Klawonn M. Lanser J. Weber OOD 21 6 0 13 Feb 2023
MGIC: Multigrid-in-Channels Neural Network Architectures Moshe Eliasof Jonathan Ephrath Lars Ruthotto Eran Treister 18 7 0 17 Nov 2020
On Large-Batch Training for Deep Learning: Generalization Gap and Sharp Minima N. Keskar Dheevatsa Mudigere J. Nocedal M. Smelyanskiy P. T. P. Tang ODL 273 2,886 0 15 Sep 2016