Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions

28 October 2022

Papers citing "Improving Lipschitz-Constrained Neural Networks by Learning Activation Functions"

43 / 43 papers shown

Title
Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective Bohang Zhang Du Jiang Di He Liwei Wang OOD 59 49 0 04 Oct 2022
Kantorovich Strikes Back! Wasserstein GANs are not Optimal Transport? Alexander Korotin Alexander Kolesov Evgeny Burnaev OT 44 26 0 15 Jun 2022
Approximation of Lipschitz Functions using Deep Spline Neural Networks Sebastian Neumayer Alexis Goujon Pakshal Bohra M. Unser 55 16 0 13 Apr 2022
Sparsest Univariate Learning Models Under Lipschitz Constraint Shayan Aziznejad Thomas Debarre M. Unser 35 4 0 27 Dec 2021
Gradient Step Denoiser for convergent Plug-and-Play Samuel Hurault Arthur Leclaire Nicolas Papadakis 51 95 0 07 Oct 2021
SwinIR: Image Restoration Using Swin Transformer Christos Sakaridis Jie Cao Guolei Sun Peng Sun Luc Van Gool Radu Timofte ViT 173 2,862 0 23 Aug 2021
Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100 Sahil Singla Surbhi Singla Soheil Feizi AAML 59 55 0 05 Aug 2021
CLIP: Cheap Lipschitz Training of Neural Networks Leon Bungert René Raab Tim Roith Leo Schwinn Daniel Tenbrinck 44 32 0 23 Mar 2021
Towards Certifying L-infinity Robustness using Neural Networks with L-inf-dist Neurons Bohang Zhang Tianle Cai Zhou Lu Di He Liwei Wang OOD 51 49 0 10 Feb 2021
Convolutional Proximal Neural Networks and Plug-and-Play Algorithms J. Hertrich Sebastian Neumayer Gabriele Steidl 42 58 0 04 Nov 2020
Stabilizing Invertible Neural Networks Using Mixture Models Paul Hagemann Sebastian Neumayer 31 39 0 07 Sep 2020
Learned convex regularizers for inverse problems Subhadip Mukherjee Sören Dittmer Zakhar Shumaylov Sebastian Lunz Ozan Oktem Carola-Bibiane Schönlieb 47 80 0 06 Aug 2020
Scalable Plug-and-Play ADMM with Convergence Guarantees Yu Sun Zihui Wu Xiaojian Xu B. Wohlberg Ulugbek S. Kamilov BDL 71 75 0 05 Jun 2020
Training robust neural networks using Lipschitz bounds Patricia Pauli Anne Koch J. Berberich Paul Kohler Frank Allgöwer 43 158 0 06 May 2020
Deep Neural Networks with Trainable Activations and Controlled Lipschitz Constant Shayan Aziznejad Harshit Gupta Joaquim Campos M. Unser 39 36 0 17 Jan 2020
Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks Qiyang Li Saminul Haque Cem Anil James Lucas Roger C. Grosse Joern-Henrik Jacobsen 77 114 0 03 Nov 2019
Plug-and-Play Methods Provably Converge with Properly Trained Denoisers Ernest K. Ryu Jialin Liu Sicheng Wang Xiaohan Chen Zhangyang Wang W. Yin AI4CE 58 350 0 14 May 2019
On instabilities of deep learning in image reconstruction - Does AI come at a cost? Vegard Antun F. Renna C. Poon Ben Adcock A. Hansen 48 601 0 14 Feb 2019
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI Jure Zbontar Florian Knoll Anuroop Sriram Tullie Murrell Zhengnan Huang ... Erich Owens C. L. Zitnick M. Recht D. Sodickson Yvonne W. Lui OOD 54 836 0 21 Nov 2018
Sorting out Lipschitz function approximation Cem Anil James Lucas Roger C. Grosse 74 319 0 13 Nov 2018
Limitations of the Lipschitz constant as a defense against adversarial examples Todd P. Huster C. Chiang R. Chadha AAML 32 84 0 25 Jul 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 90 1,772 0 30 May 2018
Lipschitz regularity of deep neural networks: analysis and efficient estimation Kevin Scaman Aladin Virmaux 67 523 0 28 May 2018
A representer theorem for deep neural networks M. Unser 57 98 0 26 Feb 2018
Spectral Normalization for Generative Adversarial Networks Takeru Miyato Toshiki Kataoka Masanori Koyama Yuichi Yoshida ODL 153 4,421 0 16 Feb 2018
Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks Yusuke Tsuzuku Issei Sato Masashi Sugiyama AAML 99 301 0 12 Feb 2018
Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing their Input Gradients A. Ross Finale Doshi-Velez AAML 145 679 0 26 Nov 2017
ALICE: Towards Understanding Adversarial Learning for Joint Distribution Matching Chunyuan Li Hao Liu Changyou Chen Yunchen Pu Liqun Chen Ricardo Henao Lawrence Carin GAN FedML 63 220 0 05 Sep 2017
Exploring Generalization in Deep Learning Behnam Neyshabur Srinadh Bhojanapalli David A. McAllester Nathan Srebro FAtt 139 1,245 0 27 Jun 2017
Spectrally-normalized margin bounds for neural networks Peter L. Bartlett Dylan J. Foster Matus Telgarsky ODL 169 1,208 0 26 Jun 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 243 11,962 0 19 Jun 2017
Parseval Networks: Improving Robustness to Adversarial Examples Moustapha Cissé Piotr Bojanowski Edouard Grave Yann N. Dauphin Nicolas Usunier AAML 133 800 0 28 Apr 2017
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging Problems Tim Meinhardt Michael Möller C. Hazirbas Daniel Cremers 61 357 0 11 Apr 2017
Improved Training of Wasserstein GANs Ishaan Gulrajani Faruk Ahmed Martín Arjovsky Vincent Dumoulin Aaron Courville GAN 159 9,509 0 31 Mar 2017
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 150 4,224 0 12 Jun 2016
Robust Large Margin Deep Neural Networks Jure Sokolić Raja Giryes Guillermo Sapiro M. Rodrigues 64 309 0 26 May 2016
Plug-and-Play Priors for Bright Field Electron Tomography and Sparse Interpolation S. Sreehari S. Venkatakrishnan B. Wohlberg L. Drummy Jeff P. Simmons Charles A. Bouman 70 341 0 23 Dec 2015
Deep Learning with S-shaped Rectified Linear Activation Units Xiaojie Jin Chunyan Xu Jiashi Feng Yunchao Wei Junjun Xiong Shuicheng Yan 257 217 0 22 Dec 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 1.4K 76,547 0 18 May 2015
Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification Kaiming He Xinming Zhang Shaoqing Ren Jian Sun VLM 230 18,534 0 06 Feb 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.2K 149,474 0 22 Dec 2014
Learning Activation Functions to Improve Deep Neural Networks Forest Agostinelli Matthew Hoffman Peter Sadowski Pierre Baldi ODL 182 474 0 21 Dec 2014
Exact solutions to the nonlinear dynamics of learning in deep linear neural networks Andrew M. Saxe James L. McClelland Surya Ganguli ODL 143 1,830 0 20 Dec 2013