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"

50 / 329 papers shown

Title
Spectral Normalisation for Deep Reinforcement Learning: an Optimisation Perspective Florin Gogianu Tudor Berariu Mihaela Rosca Claudia Clopath L. Buşoniu Razvan Pascanu 24 53 0 11 May 2021
Analytical bounds on the local Lipschitz constants of ReLU networks Trevor Avant K. Morgansen FAtt 21 12 0 29 Apr 2021
Recurrent Equilibrium Networks: Flexible Dynamic Models with Guaranteed Stability and Robustness Max Revay Ruigang Wang I. Manchester 32 58 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 38 21 0 11 Apr 2021
Understanding the role of importance weighting for deep learning Da Xu Yuting Ye Chuanwei Ruan FAtt 39 43 0 28 Mar 2021
CLIP: Cheap Lipschitz Training of Neural Networks Leon Bungert René Raab Tim Roith Leo Schwinn Daniel Tenbrinck 32 32 0 23 Mar 2021
Deep KKL: Data-driven Output Prediction for Non-Linear Systems Steeven Janny V. Andrieu Madiha Nadri Wolf Christian Wolf AI4TS 22 13 0 23 Mar 2021
Fast Approximate Spectral Normalization for Robust Deep Neural Networks Zhixin Pan Prabhat Mishra AAML OOD 19 1 0 22 Mar 2021
Lipschitz Normalization for Self-Attention Layers with Application to Graph Neural Networks George Dasoulas Kevin Scaman Aladin Virmaux GNN 24 40 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 52 373 0 05 Mar 2021
Sparsity Aware Normalization for GANs I. Kligvasser T. Michaeli GAN 33 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 22 54 0 01 Mar 2021
Optimizing Large-Scale Hyperparameters via Automated Learning Algorithm Bin Gu Guodong Liu Yanfu Zhang Xiang Geng Heng-Chiao Huang 41 19 0 17 Feb 2021
Adversarially Robust Kernel Smoothing Jia-Jie Zhu Christina Kouridi Yassine Nemmour Bernhard Schölkopf 28 7 0 16 Feb 2021
A Law of Robustness for Weight-bounded Neural Networks Hisham Husain Borja Balle 23 1 0 16 Feb 2021
Certifiably Robust Variational Autoencoders Ben Barrett A. Camuto M. Willetts Tom Rainforth AAML DRL 29 15 0 15 Feb 2021
Depthwise Separable Convolutions Allow for Fast and Memory-Efficient Spectral Normalization Christina Runkel Christian Etmann Michael Möller Carola-Bibiane Schönlieb 22 1 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 30 41 0 10 Feb 2021
Estimation and Applications of Quantiles in Deep Binary Classification Anuj Tambwekar Anirudh Maiya S. Dhavala Snehanshu Saha UQCV 13 7 0 09 Feb 2021
Recoding latent sentence representations -- Dynamic gradient-based activation modification in RNNs Dennis Ulmer 33 0 0 03 Jan 2021
Bounding the Complexity of Formally Verifying Neural Networks: A Geometric Approach James Ferlez Yasser Shoukry 11 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 77 31 0 16 Dec 2020
A case for new neural network smoothness constraints Mihaela Rosca T. Weber Arthur Gretton S. Mohamed AAML 35 48 0 14 Dec 2020
Regularizing Action Policies for Smooth Control with Reinforcement Learning Siddharth Mysore B. Mabsout R. Mancuso Kate Saenko 39 67 0 11 Dec 2020
Certifying Incremental Quadratic Constraints for Neural Networks via Convex Optimization Navid Hashemi Justin Ruths Mahyar Fazlyab 11 22 0 10 Dec 2020
A Geometric Perspective on Self-Supervised Policy Adaptation Cristian Bodnar Karol Hausman Gabriel Dulac-Arnold Rico Jonschkowski SSL 44 5 0 14 Nov 2020
Solving Inverse Problems With Deep Neural Networks -- Robustness Included? Martin Genzel Jan Macdonald M. März AAML OOD 27 101 0 09 Nov 2020
Analytical aspects of non-differentiable neural networks G. P. Leonardi Matteo Spallanzani 17 1 0 03 Nov 2020
ControlVAE: Tuning, Analytical Properties, and Performance Analysis Huajie Shao Zhisheng Xiao Shuochao Yao Aston Zhang Shengzhong Liu Tarek F. Abdelzaher DRL 43 14 0 31 Oct 2020
The power of quantum neural networks Amira Abbas David Sutter Christa Zoufal Aurelien Lucchi Alessio Figalli Stefan Woerner 33 726 0 30 Oct 2020
Tight Second-Order Certificates for Randomized Smoothing Alexander Levine Aounon Kumar Thomas A. Goldstein S. Feizi AAML 6 16 0 20 Oct 2020
On Convergence of Nearest Neighbor Classifiers over Feature Transformations Luka Rimanic Cédric Renggli Bo-wen Li Ce Zhang 6 14 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 27 7 0 10 Oct 2020
EigenGame: PCA as a Nash Equilibrium I. Gemp Brian McWilliams Claire Vernade T. Graepel 32 46 0 01 Oct 2020
Large Norms of CNN Layers Do Not Hurt Adversarial Robustness Youwei Liang Dong Huang 22 11 0 17 Sep 2020
Finite-Sample Guarantees for Wasserstein Distributionally Robust Optimization: Breaking the Curse of Dimensionality Rui Gao 29 88 0 09 Sep 2020
Tunable Subnetwork Splitting for Model-parallelism of Neural Network Training Junxiang Wang Zheng Chai Xiangyi Chen Liang Zhao 4 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 34 31 0 07 Sep 2020
Analytical bounds on the local Lipschitz constants of affine-ReLU functions Trevor Avant K. Morgansen 8 5 0 14 Aug 2020
Adversarial Training Reduces Information and Improves Transferability M. Terzi Alessandro Achille Marco Maggipinto Gian Antonio Susto AAML 24 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 29 19 0 08 Jul 2020
Model-Aware Regularization For Learning Approaches To Inverse Problems Jaweria Amjad Zhaoyang Lyu M. Rodrigues MedIm 11 0 0 18 Jun 2020
On Lipschitz Regularization of Convolutional Layers using Toeplitz Matrix Theory Alexandre Araujo Benjamin Négrevergne Y. Chevaleyre Jamal Atif 34 0 0 15 Jun 2020
Markov-Lipschitz Deep Learning Stan Z. Li Zelin Zhang Lirong Wu 14 16 0 15 Jun 2020
Kernel Distributionally Robust Optimization Jia Jie Zhu Wittawat Jitkrittum Moritz Diehl Bernhard Schölkopf 36 16 0 12 Jun 2020
Achieving robustness in classification using optimal transport with hinge regularization M. Serrurier Franck Mamalet Alberto González Sanz Thibaut Boissin Jean-Michel Loubes E. del Barrio AAML 28 39 0 11 Jun 2020
The Lipschitz Constant of Self-Attention Hyunjik Kim George Papamakarios A. Mnih 14 134 0 08 Jun 2020
Learning disconnected manifolds: a no GANs land Ugo Tanielian Thibaut Issenhuth Elvis Dohmatob Jérémie Mary 17 35 0 08 Jun 2020
Lipschitz Bounds and Provably Robust Training by Laplacian Smoothing Vishaal Krishnan Abed AlRahman Al Makdah Fabio Pasqualetti OOD AAML 10 23 0 05 Jun 2020
Second-Order Provable Defenses against Adversarial Attacks Sahil Singla S. Feizi AAML 16 60 0 01 Jun 2020