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On Robustness of Neural Ordinary Differential Equations

12 October 2019

Vincent Y. F. Tan

Papers citing "On Robustness of Neural Ordinary Differential Equations"

24 / 24 papers shown

Title
DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling Yaohua Zang P. Koutsourelakis AI4CE 119 1 0 10 Feb 2025
Learning state and proposal dynamics in state-space models using differentiable particle filters and neural networks Benjamin Cox Santiago Segarra Victor Elvira 144 0 0 23 Nov 2024
SNODE: Spectral Discretization of Neural ODEs for System Identification A. Quaglino Marco Gallieri Jonathan Masci Jan Koutník AI4TS 99 48 0 17 Jun 2019
Neural SDE: Stabilizing Neural ODE Networks with Stochastic Noise Xuanqing Liu Tesi Xiao Si Si Qin Cao Sanjiv Kumar Cho-Jui Hsieh 100 138 0 05 Jun 2019
Augmented Neural ODEs Emilien Dupont Arnaud Doucet Yee Whye Teh BDL 157 634 0 02 Apr 2019
Feature Denoising for Improving Adversarial Robustness Cihang Xie Yuxin Wu Laurens van der Maaten Alan Yuille Kaiming He 133 915 0 09 Dec 2018
FFJORD: Free-form Continuous Dynamics for Scalable Reversible Generative Models Will Grathwohl Ricky T. Q. Chen J. Bettencourt Ilya Sutskever David Duvenaud DRL 160 881 0 02 Oct 2018
Analyzing Inverse Problems with Invertible Neural Networks Lynton Ardizzone Jakob Kruse Sebastian J. Wirkert D. Rahner E. Pellegrini R. Klessen Lena Maier-Hein Carsten Rother Ullrich Kothe 89 494 0 14 Aug 2018
Neural Ordinary Differential Equations T. Chen Yulia Rubanova J. Bettencourt David Duvenaud AI4CE 457 5,176 0 19 Jun 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 112 1,785 0 30 May 2018
Deep Defense: Training DNNs with Improved Adversarial Robustness Ziang Yan Yiwen Guo Changshui Zhang AAML 94 110 0 23 Feb 2018
Adversarial Examples that Fool both Computer Vision and Time-Limited Humans Gamaleldin F. Elsayed Shreya Shankar Brian Cheung Nicolas Papernot Alexey Kurakin Ian Goodfellow Jascha Narain Sohl-Dickstein AAML 107 263 0 22 Feb 2018
Mitigating Adversarial Effects Through Randomization Cihang Xie Jianyu Wang Zhishuai Zhang Zhou Ren Alan Yuille AAML 125 1,063 0 06 Nov 2017
Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations Yiping Lu Aoxiao Zhong Quanzheng Li Bin Dong 213 505 0 27 Oct 2017
ZOO: Zeroth Order Optimization based Black-box Attacks to Deep Neural Networks without Training Substitute Models Pin-Yu Chen Huan Zhang Yash Sharma Jinfeng Yi Cho-Jui Hsieh AAML 106 1,887 0 14 Aug 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 321 12,151 0 19 Jun 2017
Ensemble Adversarial Training: Attacks and Defenses Florian Tramèr Alexey Kurakin Nicolas Papernot Ian Goodfellow Dan Boneh Patrick McDaniel AAML 185 2,731 0 19 May 2017
PolyNet: A Pursuit of Structural Diversity in Very Deep Networks Xingcheng Zhang Zhizhong Li Chen Change Loy Dahua Lin MDE 65 260 0 17 Nov 2016
Towards Evaluating the Robustness of Neural Networks Nicholas Carlini D. Wagner OOD AAML 282 8,587 0 16 Aug 2016
Robust Large Margin Deep Neural Networks Jure Sokolić Raja Giryes Guillermo Sapiro M. Rodrigues 76 309 0 26 May 2016
FractalNet: Ultra-Deep Neural Networks without Residuals Gustav Larsson Michael Maire Gregory Shakhnarovich 165 941 0 24 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.3K 194,641 0 10 Dec 2015
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 282 19,145 0 20 Dec 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 293 14,978 1 21 Dec 2013