Efficient Neural Network Robustness Certification with General Activation Functions

2 November 2018

Papers citing "Efficient Neural Network Robustness Certification with General Activation Functions"

50 / 177 papers shown

Title
Robustness of Graph Neural Networks at Scale Simon Geisler Tobias Schmidt Hakan cSirin Daniel Zügner Aleksandar Bojchevski Stephan Günnemann AAML 30 126 0 26 Oct 2021
Trustworthy AI: From Principles to Practices Bo-wen Li Peng Qi Bo Liu Shuai Di Jingen Liu Jiquan Pei Jinfeng Yi Bowen Zhou 119 357 0 04 Oct 2021
Neural Network Verification in Control M. Everett AAML 34 16 0 30 Sep 2021
ROMAX: Certifiably Robust Deep Multiagent Reinforcement Learning via Convex Relaxation Chuangchuang Sun Dong-Ki Kim Jonathan P. How AAML 35 19 0 14 Sep 2021
Shared Certificates for Neural Network Verification Marc Fischer C. Sprecher Dimitar I. Dimitrov Gagandeep Singh Martin Vechev AAML 28 12 0 01 Sep 2021
The Second International Verification of Neural Networks Competition (VNN-COMP 2021): Summary and Results Stanley Bak Changliu Liu Taylor T. Johnson NAI 30 112 0 31 Aug 2021
Reachability Analysis of Neural Feedback Loops M. Everett Golnaz Habibi Chuangchuang Sun Jonathan P. How 19 53 0 09 Aug 2021
Neural Network Branch-and-Bound for Neural Network Verification Florian Jaeckle Jingyue Lu M. P. Kumar 18 8 0 27 Jul 2021
On the Certified Robustness for Ensemble Models and Beyond Zhuolin Yang Linyi Li Xiaojun Xu B. Kailkhura Tao Xie Bo-wen Li AAML 29 48 0 22 Jul 2021
GoTube: Scalable Stochastic Verification of Continuous-Depth Models Sophie Gruenbacher Mathias Lechner Ramin Hasani Daniela Rus T. Henzinger S. Smolka Radu Grosu 26 17 0 18 Jul 2021
Provable Lipschitz Certification for Generative Models Matt Jordan A. Dimakis 22 14 0 06 Jul 2021
Scalable Certified Segmentation via Randomized Smoothing Marc Fischer Maximilian Baader Martin Vechev 20 38 0 01 Jul 2021
POLAR: A Polynomial Arithmetic Framework for Verifying Neural-Network Controlled Systems Chao Huang Jiameng Fan Zhilu Wang Yixuan Wang Weichao Zhou Jiajun Li Xin Chen Wenchao Li Qi Zhu 40 48 0 25 Jun 2021
Failing with Grace: Learning Neural Network Controllers that are Boundedly Unsafe Panagiotis Vlantis Leila J. Bridgeman Michael M. Zavlanos 40 0 0 22 Jun 2021
DeepSplit: Scalable Verification of Deep Neural Networks via Operator Splitting Shaoru Chen Eric Wong Zico Kolter Mahyar Fazlyab 47 15 0 16 Jun 2021
DNNV: A Framework for Deep Neural Network Verification David Shriver Sebastian G. Elbaum Matthew B. Dwyer 21 31 0 26 May 2021
Random and Adversarial Bit Error Robustness: Energy-Efficient and Secure DNN Accelerators David Stutz Nandhini Chandramoorthy Matthias Hein Bernt Schiele AAML MQ 24 18 0 16 Apr 2021
Relating Adversarially Robust Generalization to Flat Minima David Stutz Matthias Hein Bernt Schiele OOD 41 65 0 09 Apr 2021
A Review of Formal Methods applied to Machine Learning Caterina Urban Antoine Miné 46 55 0 06 Apr 2021
Adaptive Clustering of Robust Semantic Representations for Adversarial Image Purification S. Silva Arun Das I. Scarff Peyman Najafirad AAML 20 1 0 05 Apr 2021
PRIMA: General and Precise Neural Network Certification via Scalable Convex Hull Approximations Mark Niklas Muller Gleb Makarchuk Gagandeep Singh Markus Püschel Martin Vechev 41 90 0 05 Mar 2021
Adversarial Robustness with Non-uniform Perturbations Ece Naz Erdemir Jeffrey Bickford Luca Melis Sergul Aydore AAML 24 26 0 24 Feb 2021
Make Sure You're Unsure: A Framework for Verifying Probabilistic Specifications Leonard Berrada Sumanth Dathathri Krishnamurthy Dvijotham Robert Stanforth Rudy Bunel J. Uesato Sven Gowal M. P. Kumar AAML OOD 30 17 0 18 Feb 2021
Globally-Robust Neural Networks Klas Leino Zifan Wang Matt Fredrikson AAML OOD 80 126 0 16 Feb 2021
On the Paradox of Certified Training Nikola Jovanović Mislav Balunović Maximilian Baader Martin Vechev OOD 28 13 0 12 Feb 2021
Fast Training of Provably Robust Neural Networks by SingleProp Akhilan Boopathy Tsui-Wei Weng Sijia Liu Pin-Yu Chen Gaoyuan Zhang Luca Daniel AAML 11 7 0 01 Feb 2021
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification Brendon G. Anderson Ziye Ma Jingqi Li Somayeh Sojoudi 60 1 0 22 Jan 2021
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary Huan Zhang Hongge Chen Duane S. Boning Cho-Jui Hsieh 67 163 0 21 Jan 2021
DSRNA: Differentiable Search of Robust Neural Architectures Ramtin Hosseini Xingyi Yang P. Xie OOD AAML 29 50 0 11 Dec 2020
Almost Tight L0-norm Certified Robustness of Top-k Predictions against Adversarial Perturbations Jinyuan Jia Binghui Wang Xiaoyu Cao Hongbin Liu Neil Zhenqiang Gong 21 24 0 15 Nov 2020
An efficient nonconvex reformulation of stagewise convex optimization problems Rudy Bunel Oliver Hinder Srinadh Bhojanapalli Krishnamurthy Dvijotham Dvijotham OffRL 35 14 0 27 Oct 2020
Global Optimization of Objective Functions Represented by ReLU Networks Christopher A. Strong Haoze Wu Aleksandar Zeljić Kyle D. Julian Guy Katz Clark W. Barrett Mykel J. Kochenderfer AAML 17 33 0 07 Oct 2020
Adversarial Boot Camp: label free certified robustness in one epoch Ryan Campbell Chris Finlay Adam M. Oberman AAML 28 0 0 05 Oct 2020
Analysis of three dimensional potential problems in non-homogeneous media with physics-informed deep collocation method using material transfer learning and sensitivity analysis Hongwei Guo X. Zhuang Pengwan Chen N. Alajlan Timon Rabczuk 27 58 0 03 Oct 2020
Data-Driven Certification of Neural Networks with Random Input Noise Brendon G. Anderson Somayeh Sojoudi AAML 17 11 0 02 Oct 2020
Assessing Robustness of Text Classification through Maximal Safe Radius Computation Emanuele La Malfa Min Wu Luca Laurenti Benjie Wang Anthony Hartshorn Marta Z. Kwiatkowska AAML 20 18 0 01 Oct 2020
SoK: Certified Robustness for Deep Neural Networks Linyi Li Tao Xie Bo-wen Li AAML 38 128 0 09 Sep 2020
Adversarial Training and Provable Robustness: A Tale of Two Objectives Jiameng Fan Wenchao Li AAML 23 20 0 13 Aug 2020
Robust Deep Reinforcement Learning through Adversarial Loss Tuomas P. Oikarinen Wang Zhang Alexandre Megretski Luca Daniel Tsui-Wei Weng AAML 49 94 0 05 Aug 2020
Scaling Polyhedral Neural Network Verification on GPUs Christoph Müller F. Serre Gagandeep Singh Markus Püschel Martin Vechev AAML 29 56 0 20 Jul 2020
The Convex Relaxation Barrier, Revisited: Tightened Single-Neuron Relaxations for Neural Network Verification Christian Tjandraatmadja Ross Anderson Joey Huchette Will Ma Krunal Patel J. Vielma AAML 27 89 0 24 Jun 2020
Verifying Individual Fairness in Machine Learning Models Philips George John Deepak Vijaykeerthy Diptikalyan Saha FaML 27 57 0 21 Jun 2020
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness Mohammadamin Tavakoli Forest Agostinelli Pierre Baldi AAML FAtt 36 39 0 16 Jun 2020
Probabilistic Safety for Bayesian Neural Networks Matthew Wicker Luca Laurenti A. Patané Marta Z. Kwiatkowska AAML 14 52 0 21 Apr 2020
NNV: The Neural Network Verification Tool for Deep Neural Networks and Learning-Enabled Cyber-Physical Systems Hoang-Dung Tran Xiaodong Yang Diego Manzanas Lopez Patrick Musau L. V. Nguyen Weiming Xiang Stanley Bak Taylor T. Johnson 34 239 0 12 Apr 2020
Verification of Deep Convolutional Neural Networks Using ImageStars Hoang-Dung Tran Stanley Bak Weiming Xiang Taylor T. Johnson AAML 20 127 0 12 Apr 2020
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning Michael Everett Bjorn Lutjens Jonathan P. How AAML 20 41 0 11 Apr 2020
Robust Deep Reinforcement Learning against Adversarial Perturbations on State Observations Huan Zhang Hongge Chen Chaowei Xiao Bo-wen Li Mingyan D. Liu Duane S. Boning Cho-Jui Hsieh AAML 47 261 0 19 Mar 2020
Exploiting Verified Neural Networks via Floating Point Numerical Error Kai Jia Martin Rinard AAML 37 34 0 06 Mar 2020
Learning Certified Individually Fair Representations Anian Ruoss Mislav Balunović Marc Fischer Martin Vechev FaML 15 92 0 24 Feb 2020