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A case for new neural network smoothness constraints
v1v2v3 (latest)

A case for new neural network smoothness constraints

14 December 2020
Mihaela Rosca
T. Weber
Arthur Gretton
S. Mohamed
    AAML
ArXiv (abs)PDFHTML

Papers citing "A case for new neural network smoothness constraints"

39 / 39 papers shown
Formal Reasoning About Confidence and Automated Verification of Neural Networks
Formal Reasoning About Confidence and Automated Verification of Neural Networks
Mohammad Afzal
S. Akshay
Ashutosh Gupta
Ashutosh Gupta
AAML
108
0
0
10 Nov 2025
"Your Doctor is Spying on You": An Analysis of Data Practices in Mobile Healthcare Applications
"Your Doctor is Spying on You": An Analysis of Data Practices in Mobile Healthcare Applications
Luke Stevenson
Sanchari Das
188
1
0
07 Oct 2025
On the Complexity-Faithfulness Trade-off of Gradient-Based Explanations
On the Complexity-Faithfulness Trade-off of Gradient-Based Explanations
Amir Mehrpanah
Matteo Gamba
Kevin Smith
Hossein Azizpour
FAtt
192
0
0
14 Aug 2025
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the WildComputer Vision and Pattern Recognition (CVPR), 2025
Damien Teney
Liangze Jiang
Florin Gogianu
Ehsan Abbasnejad
1.2K
8
0
13 Mar 2025
Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation
Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain AdaptationAAAI Conference on Artificial Intelligence (AAAI), 2024
Wei Chen
Guo Ye
Yakun Wang
Zhao Zhang
Libang Zhang
Daxin Wang
Qing Cui
Fuzhen Zhuang
754
13
0
17 Jan 2025
Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression
Optimality and Adaptivity of Deep Neural Features for Instrumental Variable RegressionInternational Conference on Learning Representations (ICLR), 2025
Juno Kim
Dimitri Meunier
Arthur Gretton
Taiji Suzuki
Zhu Li
269
3
0
10 Jan 2025
An Unsupervised Approach to Achieve Supervised-Level Explainability in
  Healthcare Records
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records
Joakim Edin
Maria Maistro
Lars Maaløe
Lasse Borgholt
Jakob Drachmann Havtorn
Tuukka Ruotsalo
FAtt
289
19
0
13 Jun 2024
The Impact of Geometric Complexity on Neural Collapse in Transfer
  Learning
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning
Michael Munn
Benoit Dherin
Javier Gonzalvo
AAML
333
5
0
24 May 2024
From Robustness to Improved Generalization and Calibration in
  Pre-trained Language Models
From Robustness to Improved Generalization and Calibration in Pre-trained Language Models
Josip Jukić
Jan Snajder
433
2
0
31 Mar 2024
WARM: On the Benefits of Weight Averaged Reward Models
WARM: On the Benefits of Weight Averaged Reward ModelsInternational Conference on Machine Learning (ICML), 2024
Alexandre Ramé
Nino Vieillard
Léonard Hussenot
Robert Dadashi
Geoffrey Cideron
Olivier Bachem
Johan Ferret
463
136
0
22 Jan 2024
How Smooth Is Attention?
How Smooth Is Attention?
Valérie Castin
Pierre Ablin
Gabriel Peyré
AAML
398
34
0
22 Dec 2023
Towards Architecture-Agnostic Untrained Network Priors for Image
  Reconstruction with Frequency Regularization
Towards Architecture-Agnostic Untrained Network Priors for Image Reconstruction with Frequency RegularizationEuropean Conference on Computer Vision (ECCV), 2023
Yilin Liu
Yunkui Pang
Jiang-Ping Li
Yong Chen
P. Yap
455
3
0
15 Dec 2023
Out-of-Distribution Detection by Leveraging Between-Layer Transformation
  Smoothness
Out-of-Distribution Detection by Leveraging Between-Layer Transformation SmoothnessInternational Conference on Learning Representations (ICLR), 2023
Fran Jelenić
Josip Jukić
Martin Tutek
Mate Puljiz
Jan vSnajder
OODD
322
12
0
04 Oct 2023
Certified Robust Models with Slack Control and Large Lipschitz Constants
Certified Robust Models with Slack Control and Large Lipschitz Constants
M. Losch
David Stutz
Bernt Schiele
Mario Fritz
232
4
0
12 Sep 2023
Towards Stability of Autoregressive Neural Operators
Towards Stability of Autoregressive Neural Operators
Michael McCabe
P. Harrington
Shashank Subramanian
Jed Brown
AI4CE
482
43
0
18 Jun 2023
Data Interpolants -- That's What Discriminators in Higher-order
  Gradient-regularized GANs Are
Data Interpolants -- That's What Discriminators in Higher-order Gradient-regularized GANs Are
Aadithya Srikanth
C. Seelamantula
289
4
0
01 Jun 2023
PDE+: Enhancing Generalization via PDE with Adaptive Distributional
  Diffusion
PDE+: Enhancing Generalization via PDE with Adaptive Distributional DiffusionAAAI Conference on Artificial Intelligence (AAAI), 2023
Yige Yuan
Bingbing Xu
Bo Lin
Liang Hou
Fei Sun
Huawei Shen
Xueqi Cheng
DiffM
406
6
0
25 May 2023
Direct Parameterization of Lipschitz-Bounded Deep Networks
Direct Parameterization of Lipschitz-Bounded Deep NetworksInternational Conference on Machine Learning (ICML), 2023
Ruigang Wang
I. Manchester
571
63
0
27 Jan 2023
Boundary-Aware Uncertainty for Feature Attribution Explainers
Boundary-Aware Uncertainty for Feature Attribution ExplainersInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Davin Hill
A. Masoomi
Max Torop
S. Ghimire
Jennifer Dy
FAtt
628
9
0
05 Oct 2022
Learning Globally Smooth Functions on Manifolds
Learning Globally Smooth Functions on ManifoldsInternational Conference on Machine Learning (ICML), 2022
J. Cerviño
Luiz F. O. Chamon
B. Haeffele
René Vidal
Alejandro Ribeiro
578
6
0
01 Oct 2022
Why neural networks find simple solutions: the many regularizers of
  geometric complexity
Why neural networks find simple solutions: the many regularizers of geometric complexityNeural Information Processing Systems (NeurIPS), 2022
Benoit Dherin
Michael Munn
M. Rosca
David Barrett
408
44
0
27 Sep 2022
Deep Double Descent via Smooth Interpolation
Deep Double Descent via Smooth Interpolation
Matteo Gamba
Erik Englesson
Mårten Björkman
Hossein Azizpour
723
13
0
21 Sep 2022
SmOOD: Smoothness-based Out-of-Distribution Detection Approach for
  Surrogate Neural Networks in Aircraft Design
SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft DesignInternational Conference on Automated Software Engineering (ASE), 2022
Houssem Ben Braiek
Ali Tfaily
Foutse Khomh
Thomas Reid
Ciro Guida
327
0
0
07 Sep 2022
Monitoring Vegetation From Space at Extremely Fine Resolutions via
  Coarsely-Supervised Smooth U-Net
Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-NetInternational Joint Conference on Artificial Intelligence (IJCAI), 2022
Joshua Fan
Di Chen
J. Wen
Ying Sun
Daniel Schwalbe-Koda
188
3
0
16 Jul 2022
Lipschitz Continuity Retained Binary Neural Network
Lipschitz Continuity Retained Binary Neural NetworkEuropean Conference on Computer Vision (ECCV), 2022
Yuzhang Shang
Dan Xu
Bin Duan
Ziliang Zong
Liqiang Nie
Yan Yan
325
27
0
13 Jul 2022
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels
Stabilizing Off-Policy Deep Reinforcement Learning from PixelsInternational Conference on Machine Learning (ICML), 2022
Edoardo Cetin
Philip J. Ball
Steve Roberts
Oya Celiktutan
249
42
0
03 Jul 2022
Distributional Gaussian Processes Layers for Out-of-Distribution
  Detection
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
S. Popescu
D. Sharp
James H. Cole
Konstantinos Kamnitsas
Ben Glocker
OOD
326
1
0
27 Jun 2022
Analyzing Explainer Robustness via Probabilistic Lipschitzness of
  Prediction Functions
Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction FunctionsInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022
Zulqarnain Khan
Davin Hill
A. Masoomi
Joshua Bone
Jennifer Dy
AAML
521
7
0
24 Jun 2022
Learning Smooth Neural Functions via Lipschitz Regularization
Learning Smooth Neural Functions via Lipschitz RegularizationInternational Conference on Computer Graphics and Interactive Techniques (SIGGRAPH), 2022
Hsueh-Ti Derek Liu
Francis Williams
Alec Jacobson
Sanja Fidler
Or Litany
439
124
0
16 Feb 2022
The Geometric Occam's Razor Implicit in Deep Learning
The Geometric Occam's Razor Implicit in Deep Learning
Benoit Dherin
Micheal Munn
David Barrett
291
8
0
30 Nov 2021
Learning to Assimilate in Chaotic Dynamical Systems
Learning to Assimilate in Chaotic Dynamical SystemsNeural Information Processing Systems (NeurIPS), 2021
Michael McCabe
Jed Brown
AI4TS
313
17
0
01 Nov 2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization
RoMA: Robust Model Adaptation for Offline Model-based Optimization
Sihyun Yu
SungSoo Ahn
Le Song
Jinwoo Shin
OffRL
284
49
0
27 Oct 2021
On the Practicality of Deterministic Epistemic Uncertainty
On the Practicality of Deterministic Epistemic Uncertainty
Janis Postels
Mattia Segu
Tao Sun
Luca Sieber
Luc Van Gool
Feng Yu
Federico Tombari
UQCV
448
76
0
01 Jul 2021
Can convolutional ResNets approximately preserve input distances? A
  frequency analysis perspective
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective
Lewis Smith
Joost R. van Amersfoort
Haiwen Huang
Stephen J. Roberts
Y. Gal
265
7
0
04 Jun 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation
  Perspective
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation PerspectiveInternational Conference on Machine Learning (ICML), 2021
Florin Gogianu
Tudor Berariu
Mihaela Rosca
Claudia Clopath
L. Buşoniu
Razvan Pascanu
368
66
0
11 May 2021
On Feature Collapse and Deep Kernel Learning for Single Forward Pass
  Uncertainty
On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty
Joost R. van Amersfoort
Lewis Smith
Andrew Jesson
Oscar Key
Y. Gal
UQCV
469
122
0
22 Feb 2021
Hierarchical Gaussian Processes with Wasserstein-2 Kernels
Hierarchical Gaussian Processes with Wasserstein-2 Kernels
S. Popescu
D. Sharp
James H. Cole
Ben Glocker
355
5
0
28 Oct 2020
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial
  Imitation Learning
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning
Lionel Blondé
Pablo Strasser
Alexandros Kalousis
471
24
0
28 Jun 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep
  Learning via Distance Awareness
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
Jeremiah Zhe Liu
Zi Lin
Shreyas Padhy
Dustin Tran
Tania Bedrax-Weiss
Balaji Lakshminarayanan
UQCVBDL
973
541
0
17 Jun 2020
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