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2505.12003
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Approximation theory for 1-Lipschitz ResNets
17 May 2025
Davide Murari
Takashi Furuya
Carola-Bibiane Schönlieb
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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
76
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
109
56
0
25 Oct 2021
Orthogonalizing Convolutional Layers with the Cayley Transform
Asher Trockman
J. Zico Kolter
80
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
69
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
1