Deep Neural Networks Motivated by Partial Differential Equations

12 April 2018

Papers citing "Deep Neural Networks Motivated by Partial Differential Equations"

24 / 24 papers shown

Title
Flowing Through Layers: A Continuous Dynamical Systems Perspective on Transformers Jacob Fein-Ashley AI4CE 104 0 0 08 Feb 2025
Scale generalisation properties of extended scale-covariant and scale-invariant Gaussian derivative networks on image datasets with spatial scaling variations Andrzej Perzanowski Tony Lindeberg 119 1 0 17 Sep 2024
Learning Regularization for Graph Inverse Problems Moshe Eliasof Md Shahriar Rahim Siddiqui Carola-Bibiane Schönlieb Eldad Haber GNN 160 0 0 19 Aug 2024
Large-time asymptotics in deep learning Carlos Esteve Borjan Geshkovski Dario Pighin Enrique Zuazua 332 34 0 06 Aug 2020
LeanConvNets: Low-cost Yet Effective Convolutional Neural Networks Jonathan Ephrath Moshe Eliasof Lars Ruthotto E. Haber Eran Treister 99 16 0 29 Oct 2019
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 411 5,103 0 19 Jun 2018
Multi-level Residual Networks from Dynamical Systems View B. Chang Lili Meng E. Haber Frederick Tung David Begert 77 172 0 27 Oct 2017
Maximum Principle Based Algorithms for Deep Learning Qianxiao Li Long Chen Cheng Tai E. Weinan 99 223 0 26 Oct 2017
Reversible Architectures for Arbitrarily Deep Residual Neural Networks B. Chang Lili Meng E. Haber Lars Ruthotto David Begert E. Holtham AI4CE 74 264 0 12 Sep 2017
The Reversible Residual Network: Backpropagation Without Storing Activations Aidan Gomez Mengye Ren R. Urtasun Roger C. Grosse 74 548 0 14 Jul 2017
DeepXplore: Automated Whitebox Testing of Deep Learning Systems Kexin Pei Yinzhi Cao Junfeng Yang Suman Jana AAML 82 1,366 0 18 May 2017
Stable Architectures for Deep Neural Networks E. Haber Lars Ruthotto 145 728 0 09 May 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 136 807 0 28 Apr 2017
Deep Relaxation: partial differential equations for optimizing deep neural networks Pratik Chaudhari Adam M. Oberman Stanley Osher Stefano Soatto G. Carlier 135 154 0 17 Apr 2017
Learning across scales - A multiscale method for Convolution Neural Networks E. Haber Lars Ruthotto E. Holtham Seong-Hwan Jun 50 23 0 06 Mar 2017
Universal adversarial perturbations Seyed-Mohsen Moosavi-Dezfooli Alhussein Fawzi Omar Fawzi P. Frossard AAML 136 2,528 0 26 Oct 2016
Wide Residual Networks Sergey Zagoruyko N. Komodakis 337 7,984 0 23 May 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,182 0 16 Mar 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 193,878 0 10 Dec 2015
A General Framework for Constrained Bayesian Optimization using Information-based Search José Miguel Hernández-Lobato M. Gelbart Ryan P. Adams Matthew W. Hoffman Zoubin Ghahramani 50 165 0 30 Nov 2015
Convolutional Clustering for Unsupervised Learning Aysegül Dündar Jonghoon Jin Eugenio Culurciello SSL 41 84 0 19 Nov 2015
Trainable Nonlinear Reaction Diffusion: A Flexible Framework for Fast and Effective Image Restoration Yunjin Chen Thomas Pock DiffM 50 1,188 0 12 Aug 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift Sergey Ioffe Christian Szegedy OOD 463 43,289 0 11 Feb 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 277 19,049 0 20 Dec 2014