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Do Residual Neural Networks discretize Neural Ordinary Differential
  Equations?

Do Residual Neural Networks discretize Neural Ordinary Differential Equations?

29 May 2022
Michael E. Sander
Pierre Ablin
Gabriel Peyré
ArXivPDFHTML

Papers citing "Do Residual Neural Networks discretize Neural Ordinary Differential Equations?"

17 / 17 papers shown
Title
Statistical physics analysis of graph neural networks: Approaching optimality in the contextual stochastic block model
O. Duranthon
L. Zdeborová
43
0
0
03 Mar 2025
Topological Neural Networks go Persistent, Equivariant, and Continuous
Topological Neural Networks go Persistent, Equivariant, and Continuous
Yogesh Verma
Amauri H Souza
Vikas K. Garg
AI4CE
38
4
0
05 Jun 2024
Deep linear networks for regression are implicitly regularized towards
  flat minima
Deep linear networks for regression are implicitly regularized towards flat minima
Pierre Marion
Lénaic Chizat
ODL
26
5
0
22 May 2024
Generalization of Scaled Deep ResNets in the Mean-Field Regime
Generalization of Scaled Deep ResNets in the Mean-Field Regime
Yihang Chen
Fanghui Liu
Yiping Lu
Grigorios G. Chrysos
V. Cevher
33
2
0
14 Mar 2024
Differential Equations for Continuous-Time Deep Learning
Differential Equations for Continuous-Time Deep Learning
Lars Ruthotto
AI4TS
AI4CE
SyDa
BDL
30
7
0
08 Jan 2024
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers
M. Terris
Thomas Moreau
24
0
0
30 Nov 2023
Approximating Langevin Monte Carlo with ResNet-like Neural Network
  architectures
Approximating Langevin Monte Carlo with ResNet-like Neural Network architectures
Charles Miranda
Janina Enrica Schutte
David Sommer
Martin Eigel
26
3
0
06 Nov 2023
Implicit regularization of deep residual networks towards neural ODEs
Implicit regularization of deep residual networks towards neural ODEs
P. Marion
Yu-Han Wu
Michael E. Sander
Gérard Biau
27
14
0
03 Sep 2023
A Novel Convolutional Neural Network Architecture with a Continuous
  Symmetry
A Novel Convolutional Neural Network Architecture with a Continuous Symmetry
Y. Liu
Han-Juan Shao
Bing Bai
AI4CE
24
2
0
03 Aug 2023
PAC bounds of continuous Linear Parameter-Varying systems related to
  neural ODEs
PAC bounds of continuous Linear Parameter-Varying systems related to neural ODEs
Dániel Rácz
M. Petreczky
Bálint Daróczy
55
0
0
07 Jul 2023
Vocabulary for Universal Approximation: A Linguistic Perspective of
  Mapping Compositions
Vocabulary for Universal Approximation: A Linguistic Perspective of Mapping Compositions
Yongqiang Cai
CoGe
75
6
0
20 May 2023
Generalization bounds for neural ordinary differential equations and
  deep residual networks
Generalization bounds for neural ordinary differential equations and deep residual networks
P. Marion
30
18
0
11 May 2023
Asymptotic Analysis of Deep Residual Networks
Asymptotic Analysis of Deep Residual Networks
R. Cont
Alain Rossier
Renyuan Xu
19
4
0
15 Dec 2022
Vanilla Feedforward Neural Networks as a Discretization of Dynamical
  Systems
Vanilla Feedforward Neural Networks as a Discretization of Dynamical Systems
Yifei Duan
Liang Li
Guanghua Ji
Yongqiang Cai
21
5
0
22 Sep 2022
Scaling ResNets in the Large-depth Regime
Scaling ResNets in the Large-depth Regime
P. Marion
Adeline Fermanian
Gérard Biau
Jean-Philippe Vert
26
16
0
14 Jun 2022
ResNet strikes back: An improved training procedure in timm
ResNet strikes back: An improved training procedure in timm
Ross Wightman
Hugo Touvron
Hervé Jégou
AI4TS
209
487
0
01 Oct 2021
Lagrangian Neural Networks
Lagrangian Neural Networks
M. Cranmer
S. Greydanus
Stephan Hoyer
Peter W. Battaglia
D. Spergel
S. Ho
PINN
130
422
0
10 Mar 2020
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