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Deep Neural Networks with Trainable Activations and Controlled Lipschitz
  Constant

Deep Neural Networks with Trainable Activations and Controlled Lipschitz Constant

17 January 2020
Shayan Aziznejad
Harshit Gupta
Joaquim Campos
M. Unser
ArXivPDFHTML

Papers citing "Deep Neural Networks with Trainable Activations and Controlled Lipschitz Constant"

13 / 13 papers shown
Title
1-Lipschitz Neural Networks are more expressive with N-Activations
1-Lipschitz Neural Networks are more expressive with N-Activations
Bernd Prach
Christoph H. Lampert
AAML
FAtt
26
0
0
10 Nov 2023
Deep Stochastic Mechanics
Deep Stochastic Mechanics
Elena Orlova
Aleksei Ustimenko
Ruoxi Jiang
Peter Y. Lu
Rebecca Willett
DiffM
54
0
0
31 May 2023
Uncertainty Estimation and Out-of-Distribution Detection for Deep
  Learning-Based Image Reconstruction using the Local Lipschitz
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz
D. Bhutto
Bo Zhu
J. Liu
Neha Koonjoo
H. Li
Bruce Rosen
Matthew S. Rosen
UQCV
OOD
15
2
0
12 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey
When Deep Learning Meets Polyhedral Theory: A Survey
Joey Huchette
Gonzalo Muñoz
Thiago Serra
Calvin Tsay
AI4CE
96
33
0
29 Apr 2023
Learning Gradually Non-convex Image Priors Using Score Matching
Learning Gradually Non-convex Image Priors Using Score Matching
Erich Kobler
Thomas Pock
40
3
0
21 Feb 2023
Improving Lipschitz-Constrained Neural Networks by Learning Activation
  Functions
Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions
Stanislas Ducotterd
Alexis Goujon
Pakshal Bohra
Dimitris Perdios
Sebastian Neumayer
M. Unser
37
12
0
28 Oct 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks
Approximation of Lipschitz Functions using Deep Spline Neural Networks
Sebastian Neumayer
Alexis Goujon
Pakshal Bohra
M. Unser
47
16
0
13 Apr 2022
A Quantitative Geometric Approach to Neural-Network Smoothness
A Quantitative Geometric Approach to Neural-Network Smoothness
Zehao Wang
Gautam Prakriya
S. Jha
43
13
0
02 Mar 2022
Measuring Complexity of Learning Schemes Using Hessian-Schatten Total
  Variation
Measuring Complexity of Learning Schemes Using Hessian-Schatten Total Variation
Shayan Aziznejad
Joaquim Campos
M. Unser
27
9
0
12 Dec 2021
Provable Lipschitz Certification for Generative Models
Provable Lipschitz Certification for Generative Models
Matt Jordan
A. Dimakis
22
14
0
06 Jul 2021
Augmented Shortcuts for Vision Transformers
Augmented Shortcuts for Vision Transformers
Yehui Tang
Kai Han
Chang Xu
An Xiao
Yiping Deng
Chao Xu
Yunhe Wang
ViT
19
39
0
30 Jun 2021
What Kinds of Functions do Deep Neural Networks Learn? Insights from
  Variational Spline Theory
What Kinds of Functions do Deep Neural Networks Learn? Insights from Variational Spline Theory
Rahul Parhi
Robert D. Nowak
MLT
38
70
0
07 May 2021
CLIP: Cheap Lipschitz Training of Neural Networks
CLIP: Cheap Lipschitz Training of Neural Networks
Leon Bungert
René Raab
Tim Roith
Leo Schwinn
Daniel Tenbrinck
32
32
0
23 Mar 2021
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