Approximation theory for 1-Lipschitz ResNets

17 May 2025

Papers citing "Approximation theory for 1-Lipschitz ResNets"

23 / 23 papers shown

Title
Approximation properties of neural ODEs Arturo De Marinis Davide Murari E. Celledoni Nicola Guglielmi B. Owren Francesco Tudisco 76 1 0 19 Mar 2025
1-Lipschitz Layers Compared: Memory, Speed, and Certifiable Robustness Bernd Prach Fabio Brau Giorgio Buttazzo Christoph H. Lampert 73 8 0 28 Nov 2023
Designing Stable Neural Networks using Convex Analysis and ODEs Ferdia Sherry E. Celledoni Matthias Joachim Ehrhardt Davide Murari B. Owren Carola-Bibiane Schönlieb 91 12 0 29 Jun 2023
Dynamical systems' based neural networks E. Celledoni Davide Murari B. Owren Carola-Bibiane Schönlieb Ferdia Sherry OOD 110 11 0 05 Oct 2022
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 105 56 0 04 Oct 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks Sebastian Neumayer Alexis Goujon Pakshal Bohra M. Unser 62 17 0 13 Apr 2022
A Dynamical System Perspective for Lipschitz Neural Networks Laurent Meunier Blaise Delattre Alexandre Araujo A. Allauzen 99 56 0 25 Oct 2021
Orthogonalizing Convolutional Layers with the Cayley Transform Asher Trockman J. Zico Kolter 75 115 0 14 Apr 2021
Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks George Dasoulas Kevin Scaman Aladin Virmaux GNN 74 39 0 08 Mar 2021
Convolutional Proximal Neural Networks and Plug-and-Play Algorithms J. Hertrich Sebastian Neumayer Gabriele Steidl 61 60 0 04 Nov 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 86 146 0 08 Jun 2020
Orthogonal Convolutional Neural Networks Jiayun Wang Yubei Chen Rudrasis Chakraborty Stella X. Yu 85 190 0 27 Nov 2019
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers Ernest K. Ryu Jialin Liu Sicheng Wang Xiaohan Chen Zhangyang Wang W. Yin AI4CE 76 354 0 14 May 2019
Deep Theory of Functional Connections: A New Method for Estimating the Solutions of PDEs Carl Leake 59 68 0 20 Dec 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 90 325 0 13 Nov 2018
Adversarial Regularizers in Inverse Problems Sebastian Lunz Ozan Oktem Carola-Bibiane Schönlieb GAN MedIm 107 221 0 29 May 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 164 4,445 0 16 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 105 309 0 12 Feb 2018
Optimal approximation of continuous functions by very deep ReLU networks Dmitry Yarotsky 201 294 0 10 Feb 2018
Spectral Norm Regularization for Improving the Generalizability of Deep Learning Yuichi Yoshida Takeru Miyato 83 335 0 31 May 2017
Error bounds for approximations with deep ReLU networks Dmitry Yarotsky 198 1,236 0 03 Oct 2016
Norm-preserving Orthogonal Permutation Linear Unit Activation Functions (OPLU) Artem Chernodub D. Nowicki 56 28 0 08 Apr 2016
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 289 14,968 1 21 Dec 2013