A case for new neural network smoothness constraints

14 December 2020

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

38 / 38 papers shown

Title
Do We Always Need the Simplicity Bias? Looking for Optimal Inductive Biases in the Wild Damien Teney Liangze Jiang Florin Gogianu Ehsan Abbasnejad 157 0 0 13 Mar 2025
Smoothness Really Matters: A Simple Yet Effective Approach for Unsupervised Graph Domain Adaptation Wei Chen Guo Ye Yakun Wang Zhao Zhang Libang Zhang Daxin Wang Zhiqiang Zhang Fuzhen Zhuang 91 1 0 17 Jan 2025
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 32 2 0 13 Jun 2024
The Impact of Geometric Complexity on Neural Collapse in Transfer Learning Michael Munn Benoit Dherin Javier Gonzalvo AAML 38 1 0 24 May 2024
Leveraging the Human Ventral Visual Stream to Improve Neural Network Robustness Zhenan Shao Linjian Ma Bo Li Diane M. Beck AAML 38 3 0 04 May 2024
From Robustness to Improved Generalization and Calibration in Pre-trained Language Models Josip Jukić Jan Snajder 29 0 0 31 Mar 2024
WARM: On the Benefits of Weight Averaged Reward Models Alexandre Ramé Nino Vieillard Léonard Hussenot Robert Dadashi Geoffrey Cideron Olivier Bachem Johan Ferret 102 93 0 22 Jan 2024
How Smooth Is Attention? Valérie Castin Pierre Ablin Gabriel Peyré AAML 40 9 0 22 Dec 2023
Towards Architecture-Agnostic Untrained Network Priors for Image Reconstruction with Frequency Regularization Yilin Liu Yunkui Pang Jiang-Ping Li Yong Chen P. Yap 29 0 0 15 Dec 2023
Out-of-Distribution Detection by Leveraging Between-Layer Transformation Smoothness Fran Jelenić Josip Jukić Martin Tutek Mate Puljiz Jan vSnajder OODD 22 5 0 04 Oct 2023
Certified Robust Models with Slack Control and Large Lipschitz Constants M. Losch David Stutz Bernt Schiele Mario Fritz 9 4 0 12 Sep 2023
Towards Stability of Autoregressive Neural Operators Michael McCabe P. Harrington Shashank Subramanian Jed Brown AI4CE 36 17 0 18 Jun 2023
Data Interpolants -- That's What Discriminators in Higher-order Gradient-regularized GANs Are Siddarth Asokan C. Seelamantula 24 4 0 01 Jun 2023
PDE+: Enhancing Generalization via PDE with Adaptive Distributional Diffusion Yige Yuan Bingbing Xu Bo Lin Liang Hou Fei Sun Huawei Shen Xueqi Cheng DiffM 24 4 0 25 May 2023
Direct Parameterization of Lipschitz-Bounded Deep Networks Ruigang Wang I. Manchester 22 41 0 27 Jan 2023
Boundary-Aware Uncertainty for Feature Attribution Explainers Davin Hill A. Masoomi Max Torop S. Ghimire Jennifer Dy FAtt 55 3 0 05 Oct 2022
Learning Globally Smooth Functions on Manifolds J. Cerviño Luiz F. O. Chamon B. Haeffele René Vidal Alejandro Ribeiro 27 5 0 01 Oct 2022
Why neural networks find simple solutions: the many regularizers of geometric complexity Benoit Dherin Michael Munn M. Rosca David Barrett 53 30 0 27 Sep 2022
Deep Double Descent via Smooth Interpolation Matteo Gamba Erik Englesson Marten Bjorkman Hossein Azizpour 51 10 0 21 Sep 2022
SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design Houssem Ben Braiek Ali Tfaily Foutse Khomh Thomas Reid Ciro Guida 6 0 0 07 Sep 2022
Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net Joshua Fan Di Chen J. Wen Ying Sun Carla P. Gomes 14 1 0 16 Jul 2022
Lipschitz Continuity Retained Binary Neural Network Yuzhang Shang Dan Xu Bin Duan Ziliang Zong Liqiang Nie Yan Yan 11 19 0 13 Jul 2022
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels Edoardo Cetin Philip J. Ball Steve Roberts Oya Celiktutan 30 36 0 03 Jul 2022
Distributional Gaussian Processes Layers for Out-of-Distribution Detection S. Popescu D. Sharp James H. Cole Konstantinos Kamnitsas Ben Glocker OOD 21 0 0 27 Jun 2022
Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions Zulqarnain Khan Davin Hill A. Masoomi Joshua Bone Jennifer Dy AAML 33 3 0 24 Jun 2022
Learning Smooth Neural Functions via Lipschitz Regularization Hsueh-Ti Derek Liu Francis Williams Alec Jacobson Sanja Fidler Or Litany 6 96 0 16 Feb 2022
The Geometric Occam's Razor Implicit in Deep Learning Benoit Dherin Micheal Munn David Barrett 20 6 0 30 Nov 2021
Learning to Assimilate in Chaotic Dynamical Systems Michael McCabe Jed Brown AI4TS 22 10 0 01 Nov 2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization Sihyun Yu Sungsoo Ahn Le Song Jinwoo Shin OffRL 16 31 0 27 Oct 2021
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool F. I. F. Richard Yu Federico Tombari UQCV 25 59 0 01 Jul 2021
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective Lewis Smith Joost R. van Amersfoort Haiwen Huang Stephen J. Roberts Y. Gal 12 7 0 04 Jun 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective Florin Gogianu Tudor Berariu Mihaela Rosca Claudia Clopath L. Buşoniu Razvan Pascanu 16 52 0 11 May 2021
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 11 102 0 22 Feb 2021
Hierarchical Gaussian Processes with Wasserstein-2 Kernels S. Popescu D. Sharp James H. Cole Ben Glocker 15 5 0 28 Oct 2020
Lipschitzness Is All You Need To Tame Off-policy Generative Adversarial Imitation Learning Lionel Blondé Pablo Strasser Alexandros Kalousis 25 22 0 28 Jun 2020
Representing smooth functions as compositions of near-identity functions with implications for deep network optimization Peter L. Bartlett S. Evans Philip M. Long 66 31 0 13 Apr 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 258 3,109 0 04 Nov 2016