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Lipschitz regularity of deep neural networks: analysis and efficient estimation

28 May 2018

Papers citing "Lipschitz regularity of deep neural networks: analysis and efficient estimation"

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Title
Is Homophily a Necessity for Graph Neural Networks? Yao Ma Xiaorui Liu Neil Shah Jiliang Tang 54 236 0 11 Jun 2021
What training reveals about neural network complexity Andreas Loukas Marinos Poiitis Stefanie Jegelka 70 11 0 08 Jun 2021
Learning by Transference: Training Graph Neural Networks on Growing Graphs J. Cerviño Luana Ruiz Alejandro Ribeiro GNN 59 19 0 07 Jun 2021
Measuring Generalization with Optimal Transport Ching-Yao Chuang Youssef Mroueh Kristjan Greenewald Antonio Torralba Stefanie Jegelka OT 90 27 0 07 Jun 2021
Representation Learning Beyond Linear Prediction Functions Ziping Xu Ambuj Tewari 67 21 0 31 May 2021
LipBaB: Computing exact Lipschitz constant of ReLU networks Aritra Bhowmick Meenakshi D'Souza G. S. Raghavan 40 16 0 12 May 2021
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective Florin Gogianu Tudor Berariu Mihaela Rosca Claudia Clopath L. Buşoniu Razvan Pascanu 86 56 0 11 May 2021
Analytical bounds on the local Lipschitz constants of ReLU networks Trevor Avant K. Morgansen FAtt 56 12 0 29 Apr 2021
Recurrent Equilibrium Networks: Flexible Dynamic Models with Guaranteed Stability and Robustness Max Revay Ruigang Wang I. Manchester 77 61 0 13 Apr 2021
Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networks Louis Bethune Thibaut Boissin M. Serrurier Franck Mamalet Corentin Friedrich Alberto González Sanz 109 23 0 11 Apr 2021
Understanding the role of importance weighting for deep learning Da Xu Yuting Ye Chuanwei Ruan FAtt 95 44 0 28 Mar 2021
CLIP: Cheap Lipschitz Training of Neural Networks Leon Bungert René Raab Tim Roith Leo Schwinn Daniel Tenbrinck 59 33 0 23 Mar 2021
Deep KKL: Data-driven Output Prediction for Non-Linear Systems Steeven Janny V. Andrieu Madiha Nadri Wolf Christian Wolf AI4TS 81 13 0 23 Mar 2021
Fast Approximate Spectral Normalization for Robust Deep Neural Networks Zhixin Pan Prabhat Mishra AAML OOD 25 1 0 22 Mar 2021
Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks George Dasoulas Kevin Scaman Aladin Virmaux GNN 85 39 0 08 Mar 2021
Attention is Not All You Need: Pure Attention Loses Rank Doubly Exponentially with Depth Yihe Dong Jean-Baptiste Cordonnier Andreas Loukas 163 388 0 05 Mar 2021
Sparsity Aware Normalization for GANs I. Kligvasser T. Michaeli GAN 81 6 0 03 Mar 2021
Learning Frequency Domain Approximation for Binary Neural Networks Yixing Xu Kai Han Chang Xu Yehui Tang Chunjing Xu Yunhe Wang MQ 91 55 0 01 Mar 2021
Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm Bin Gu Guodong Liu Yanfu Zhang Xiang Geng Heng-Chiao Huang 111 20 0 17 Feb 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 64 7 0 16 Feb 2021
A Law of Robustness for Weight-bounded Neural Networks Hisham Husain Borja Balle 69 1 0 16 Feb 2021
Certifiably Robust Variational Autoencoders Ben Barrett A. Camuto M. Willetts Tom Rainforth AAML DRL 77 16 0 15 Feb 2021
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization Christina Runkel Christian Etmann Michael Möller Carola-Bibiane Schönlieb 41 3 0 12 Feb 2021
CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection Hanshu Yan Jingfeng Zhang Gang Niu Jiashi Feng Vincent Y. F. Tan Masashi Sugiyama AAML 49 42 0 10 Feb 2021
Estimation and Applications of Quantiles in Deep Binary Classification Anuj Tambwekar Anirudh Maiya S. Dhavala Snehanshu Saha UQCV 27 7 0 09 Feb 2021
Recoding latent sentence representations -- Dynamic gradient-based activation modification in RNNs Dennis Ulmer 53 0 0 03 Jan 2021
Bounding the Complexity of Formally Verifying Neural Networks: A Geometric Approach James Ferlez Yasser Shoukry 58 7 0 22 Dec 2020
On The Verification of Neural ODEs with Stochastic Guarantees Sophie Gruenbacher Ramin Hasani Mathias Lechner J. Cyranka S. Smolka Radu Grosu 112 33 0 16 Dec 2020
A case for new neural network smoothness constraints Mihaela Rosca T. Weber Arthur Gretton S. Mohamed AAML 142 50 0 14 Dec 2020
Regularizing Action Policies for Smooth Control with Reinforcement Learning Siddharth Mysore B. Mabsout R. Mancuso Kate Saenko 81 69 0 11 Dec 2020
Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization Navid Hashemi Justin Ruths Mahyar Fazlyab 104 22 0 10 Dec 2020
A Geometric Perspective on Self-Supervised Policy Adaptation Cristian Bodnar Karol Hausman Gabriel Dulac-Arnold Rico Jonschkowski SSL 81 5 0 14 Nov 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 67 107 0 09 Nov 2020
Analytical aspects of non-differentiable neural networks G. P. Leonardi Matteo Spallanzani 38 1 0 03 Nov 2020
ControlVAE: Tuning, Analytical Properties, and Performance Analysis Huajie Shao Zhisheng Xiao Shuochao Yao Aston Zhang Shengzhong Liu Tarek Abdelzaher DRL 99 16 0 31 Oct 2020
The power of quantum neural networks Amira Abbas David Sutter Christa Zoufal Aurelien Lucchi Alessio Figalli Stefan Woerner 149 768 0 30 Oct 2020
Tight Second-Order Certificates for Randomized Smoothing Alexander Levine Aounon Kumar Thomas A. Goldstein Soheil Feizi AAML 55 16 0 20 Oct 2020
On Convergence of Nearest Neighbor Classifiers over Feature Transformations Luka Rimanic Cédric Renggli Yue Liu Ce Zhang 114 15 0 15 Oct 2020
Diagnosing and Preventing Instabilities in Recurrent Video Processing T. Tanay Aivar Sootla Matteo Maggioni P. Dokania Philip Torr A. Leonardis Greg Slabaugh 66 7 0 10 Oct 2020
EigenGame: PCA as a Nash Equilibrium I. Gemp Brian McWilliams Claire Vernade T. Graepel 114 48 0 01 Oct 2020
Large Norms of CNN Layers Do Not Hurt Adversarial Robustness Youwei Liang Dong Huang 48 11 0 17 Sep 2020
Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality Rui Gao 84 94 0 09 Sep 2020
Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training Junxiang Wang Zheng Chai Xiangyi Chen Liang Zhao 11 2 0 09 Sep 2020
How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks Thomas Fel David Vigouroux Rémi Cadène Thomas Serre XAI FAtt 75 31 0 07 Sep 2020
Analytical bounds on the local Lipschitz constants of affine-ReLU functions Trevor Avant K. Morgansen 61 5 0 14 Aug 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 106 23 0 22 Jul 2020
NASGEM: Neural Architecture Search via Graph Embedding Method Hsin-Pai Cheng Tunhou Zhang Yixing Zhang Shiyu Li Feng Liang Feng Yan Meng Li Vikas Chandra H. Li Yiran Chen GNN 85 19 0 08 Jul 2020
Model-Aware Regularization For Learning Approaches To Inverse Problems Jaweria Amjad Zhaoyang Lyu M. Rodrigues MedIm 18 0 0 18 Jun 2020
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory Alexandre Araujo Benjamin Négrevergne Y. Chevaleyre Jamal Atif 42 0 0 15 Jun 2020
Markov-Lipschitz Deep Learning Stan Z. Li Zelin Zhang Lirong Wu 75 16 0 15 Jun 2020