Toward Certified Robustness Against Real-World Distribution Shifts

Toward Certified Robustness Against Real-World Distribution Shifts

8 June 2022

Teruhiro Tagomori

Alexander Robey

George Pappas

Clark W. Barrett

Papers citing "Toward Certified Robustness Against Real-World Distribution Shifts"

6 / 6 papers shown

Title
Neural Network Verification with Branch-and-Bound for General Nonlinearities Zhouxing Shi Qirui Jin Zico Kolter Suman Jana Cho-Jui Hsieh Huan Zhang 34 11 0 31 May 2024
Adversarial Robustness with Semi-Infinite Constrained Learning Alexander Robey Luiz F. O. Chamon George J. Pappas Hamed Hassani Alejandro Ribeiro AAML OOD 113 42 0 29 Oct 2021
CNN-Cert: An Efficient Framework for Certifying Robustness of Convolutional Neural Networks Akhilan Boopathy Tsui-Wei Weng Pin-Yu Chen Sijia Liu Luca Daniel AAML 101 138 0 29 Nov 2018
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 72 290 0 09 Aug 2017
Reluplex: An Efficient SMT Solver for Verifying Deep Neural Networks Guy Katz Clark W. Barrett D. Dill Kyle D. Julian Mykel Kochenderfer AAML 222 1,832 0 03 Feb 2017
Safety Verification of Deep Neural Networks Xiaowei Huang M. Kwiatkowska Sen Wang Min Wu AAML 178 929 0 21 Oct 2016