On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models

30 October 2018

Sven Gowal

Krishnamurthy Dvijotham

Papers citing "On the Effectiveness of Interval Bound Propagation for Training Verifiably Robust Models"

50 / 155 papers shown

Title
Enhancing Certified Robustness via Block Reflector Orthogonal Layers and Logit Annealing Loss Bo-Han Lai Pin-Han Huang Bo-Han Kung Shang-Tse Chen 12 0 0 21 May 2025
Support is All You Need for Certified VAE Training Changming Xu Debangshu Banerjee Deepak Vasisht Gagandeep Singh AAML 44 0 0 16 Apr 2025
Adversarial Hubness in Multi-Modal Retrieval Tingwei Zhang Fnu Suya Rishi Jha Collin Zhang Vitaly Shmatikov AAML 90 1 0 18 Dec 2024
BaB-ND: Long-Horizon Motion Planning with Branch-and-Bound and Neural Dynamics Keyi Shen Jiangwei Yu Huan Zhang Yunzhu Li Yunzhu Li 103 1 0 12 Dec 2024
Average Certified Radius is a Poor Metric for Randomized Smoothing Chenhao Sun Yuhao Mao Mark Niklas Muller Martin Vechev AAML 41 0 0 09 Oct 2024
Bridging Today and the Future of Humanity: AI Safety in 2024 and Beyond Shanshan Han 87 1 0 09 Oct 2024
Make Interval Bound Propagation great again Patryk Krukowski Daniel Wilczak Jacek Tabor Anna Bielawska Przemysław Spurek OOD AAML 39 0 0 04 Oct 2024
Towards Universal Certified Robustness with Multi-Norm Training Enyi Jiang Gagandeep Singh Gagandeep Singh AAML 62 1 0 03 Oct 2024
On Using Certified Training towards Empirical Robustness Alessandro De Palma Serge Durand Zakaria Chihani François Terrier Caterina Urban OOD AAML 38 1 0 02 Oct 2024
Certified Causal Defense with Generalizable Robustness Yiran Qiao Yu Yin Chen Chen Jing Ma AAML OOD CML 63 0 0 28 Aug 2024
Discrete Randomized Smoothing Meets Quantum Computing Md. Nazmus Sakib Aman Saxena Nicola Franco Md Mashrur Arifin Stephan Günnemann AAML 34 1 0 01 Aug 2024
SPLITZ: Certifiable Robustness via Split Lipschitz Randomized Smoothing Meiyu Zhong Ravi Tandon 44 3 0 03 Jul 2024
CTBENCH: A Library and Benchmark for Certified Training Yuhao Mao Stefan Balauca Martin Vechev OOD 47 5 0 07 Jun 2024
Verifiably Robust Conformal Prediction Linus Jeary Tom Kuipers Mehran Hosseini Nicola Paoletti AAML 19 3 0 29 May 2024
Towards Certification of Uncertainty Calibration under Adversarial Attacks Cornelius Emde Francesco Pinto Thomas Lukasiewicz Philip Torr Adel Bibi AAML 47 0 0 22 May 2024
Cross-Input Certified Training for Universal Perturbations Changming Xu Gagandeep Singh AAML 33 2 0 15 May 2024
Is Adversarial Training with Compressed Datasets Effective? Tong Chen Raghavendra Selvan AAML 62 0 0 08 Feb 2024
Robust Survival Analysis with Adversarial Regularization Michael Potter Stefano Maxenti Michael Everett AAML 24 0 0 26 Dec 2023
$Improve Robustness of Reinforcement Learning against Observation Perturbations via $l_\infty$ Lipschitz Policy Networks$ Improve Robustness of Reinforcement Learning against Observation Perturbations via $l_\infty$ Lipschitz Policy Networks Buqing Nie Jingtian Ji Yangqing Fu Yue Gao 48 4 0 14 Dec 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization Mahyar Fazlyab Taha Entesari Aniket Roy Ramalingam Chellappa AAML 16 11 0 29 Sep 2023
Certifying LLM Safety against Adversarial Prompting Aounon Kumar Chirag Agarwal Suraj Srinivas Aaron Jiaxun Li S. Feizi Himabindu Lakkaraju AAML 27 167 0 06 Sep 2023
Robustness Analysis of Continuous-Depth Models with Lagrangian Techniques Sophie A. Neubauer Radu Grosu 20 0 0 23 Aug 2023
Adversarial Illusions in Multi-Modal Embeddings Tingwei Zhang Rishi Jha Eugene Bagdasaryan Vitaly Shmatikov AAML 34 8 0 22 Aug 2023
The Best Defense is a Good Offense: Adversarial Augmentation against Adversarial Attacks I. Frosio Jan Kautz AAML 29 15 0 23 May 2023
A Survey of Safety and Trustworthiness of Large Language Models through the Lens of Verification and Validation Xiaowei Huang Wenjie Ruan Wei Huang Gao Jin Yizhen Dong ... Sihao Wu Peipei Xu Dengyu Wu André Freitas Mustafa A. Mustafa ALM 49 83 0 19 May 2023
Efficient Error Certification for Physics-Informed Neural Networks Francisco Eiras Adel Bibi Rudy Bunel Krishnamurthy Dvijotham Philip Torr M. P. Kumar PINN 26 1 0 17 May 2023
When Deep Learning Meets Polyhedral Theory: A Survey Joey Huchette Gonzalo Muñoz Thiago Serra Calvin Tsay AI4CE 96 33 0 29 Apr 2023
Provable Robustness for Streaming Models with a Sliding Window Aounon Kumar Vinu Sankar Sadasivan S. Feizi OOD AAML AI4TS 21 1 0 28 Mar 2023
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection Nicola Franco Daniel Korth J. Lorenz Karsten Roscher Stephan Guennemann 33 5 0 27 Mar 2023
Boosting Verified Training for Robust Image Classifications via Abstraction Zhaodi Zhang Zhiyi Xue Yang Chen Si Liu Yueling Zhang Qingbin Liu Min Zhang 51 4 0 21 Mar 2023
Reachability Analysis of Neural Networks with Uncertain Parameters Pierre-Jean Meyer 18 0 0 14 Mar 2023
Use Perturbations when Learning from Explanations Juyeon Heo Vihari Piratla Matthew Wicker Adrian Weller AAML 40 1 0 11 Mar 2023
DeepSaDe: Learning Neural Networks that Guarantee Domain Constraint Satisfaction Kshitij Goyal Sebastijan Dumancic Hendrik Blockeel 32 2 0 02 Mar 2023
Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker Sihui Dai Wen-Luan Ding A. Bhagoji Daniel Cullina Ben Y. Zhao Haitao Zheng Prateek Mittal AAML 32 2 0 21 Feb 2023
Closed-loop Analysis of Vision-based Autonomous Systems: A Case Study C. Păsăreanu Ravi Mangal D. Gopinath Sinem Getir Yaman Calum Imrie R. Calinescu Huafeng Yu 32 29 0 06 Feb 2023
Towards Large Certified Radius in Randomized Smoothing using Quasiconcave Optimization Bo-Han Kung Shang-Tse Chen AAML 27 0 0 01 Feb 2023
Interpreting Robustness Proofs of Deep Neural Networks Debangshu Banerjee Avaljot Singh Gagandeep Singh AAML 29 5 0 31 Jan 2023
RS-Del: Edit Distance Robustness Certificates for Sequence Classifiers via Randomized Deletion Zhuoqun Huang Neil G. Marchant Keane Lucas Lujo Bauer O. Ohrimenko Benjamin I. P. Rubinstein AAML 32 15 0 31 Jan 2023
OccRob: Efficient SMT-Based Occlusion Robustness Verification of Deep Neural Networks Xingwu Guo Ziwei Zhou Yueling Zhang Guy Katz Hao Fei AAML 37 5 0 27 Jan 2023
A Robust Optimisation Perspective on Counterexample-Guided Repair of Neural Networks David Boetius Stefan Leue Tobias Sutter 38 4 0 26 Jan 2023
Interval Reachability of Nonlinear Dynamical Systems with Neural Network Controllers Saber Jafarpour Akash Harapanahalli Samuel Coogan 39 10 0 19 Jan 2023
First Three Years of the International Verification of Neural Networks Competition (VNN-COMP) Christopher Brix Mark Niklas Muller Stanley Bak Taylor T. Johnson Changliu Liu NAI 40 66 0 14 Jan 2023
Availability Adversarial Attack and Countermeasures for Deep Learning-based Load Forecasting Wangkun Xu Fei Teng AAML 24 4 0 04 Jan 2023
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 31 18 0 16 Dec 2022
Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles Shengcai Liu Fu Peng Jiaheng Zhang AAML 39 11 0 23 Nov 2022
Towards Robust Dataset Learning Yihan Wu Xinda Li Florian Kerschbaum Heng Huang Hongyang R. Zhang DD OOD 49 10 0 19 Nov 2022
Improved techniques for deterministic l2 robustness Sahil Singla S. Feizi AAML 25 10 0 15 Nov 2022
Private and Reliable Neural Network Inference Nikola Jovanović Marc Fischer Samuel Steffen Martin Vechev 22 14 0 27 Oct 2022
Evolution of Neural Tangent Kernels under Benign and Adversarial Training Noel Loo Ramin Hasani Alexander Amini Daniela Rus AAML 41 13 0 21 Oct 2022
Efficient Adversarial Training without Attacking: Worst-Case-Aware Robust Reinforcement Learning Yongyuan Liang Yanchao Sun Ruijie Zheng Furong Huang OOD AAML OffRL 28 47 0 12 Oct 2022