Data-Driven Certification of Neural Networks with Random Input Noise

Data-Driven Certification of Neural Networks with Random Input Noise

2 October 2020

Brendon G. Anderson

Somayeh Sojoudi

Papers citing "Data-Driven Certification of Neural Networks with Random Input Noise"

7 / 7 papers shown

Title
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off Yatong Bai Brendon G. Anderson Somayeh Sojoudi AAML 30 2 0 26 Nov 2023
Improving the Accuracy-Robustness Trade-Off of Classifiers via Adaptive Smoothing Yatong Bai Brendon G. Anderson Aerin Kim Somayeh Sojoudi AAML 36 18 0 29 Jan 2023
Probabilistic Verification of ReLU Neural Networks via Characteristic Functions Joshua Pilipovsky Vignesh Sivaramakrishnan Meeko Oishi Panagiotis Tsiotras 37 5 0 03 Dec 2022
Practical Convex Formulation of Robust One-hidden-layer Neural Network Training Yatong Bai Tanmay Gautam Yujie Gai Somayeh Sojoudi AAML 27 3 0 25 May 2021
Towards Optimal Branching of Linear and Semidefinite Relaxations for Neural Network Robustness Certification Brendon G. Anderson Ziye Ma Jingqi Li Somayeh Sojoudi 58 1 0 22 Jan 2021
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 88 293 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 249 1,842 0 03 Feb 2017