Towards Repairing Neural Networks Correctly

Towards Repairing Neural Networks Correctly

3 December 2020

Jun Sun

Papers citing "Towards Repairing Neural Networks Correctly"

9 / 9 papers shown

Title
PRUNE: A Patching Based Repair Framework for Certiffable Unlearning of Neural Networks Xuzhao Li Jingyi Wang Xiaohan Yuan Peixin Zhang Zhanyue Qin Zhibo Wang Kui Ren AAML MU 52 0 0 10 May 2025
Counterexample-Guided Repair of Reinforcement Learning Systems Using Safety Critics David Boetius Stefan Leue 28 0 0 24 May 2024
Safe Robot Learning in Assistive Devices through Neural Network Repair K. Majd Geoffrey Clark Tanmay Khandait Siyu Zhou S. Sankaranarayanan Georgios Fainekos H. B. Amor 19 1 0 08 Mar 2023
Verification-Aided Deep Ensemble Selection Guy Amir Tom Zelazny Guy Katz Michael Schapira AAML 30 18 0 08 Feb 2022
Minimal Multi-Layer Modifications of Deep Neural Networks Idan Refaeli Guy Katz KELM AAML 35 15 0 18 Oct 2021
Sound and Complete Neural Network Repair with Minimality and Locality Guarantees Feisi Fu Wenchao Li KELM AAML 41 26 0 14 Oct 2021
Local Repair of Neural Networks Using Optimization K. Majd Siyu Zhou H. B. Amor Georgios Fainekos S. Sankaranarayanan 18 6 0 28 Sep 2021
Output Reachable Set Estimation and Verification for Multi-Layer Neural Networks Weiming Xiang Hoang-Dung Tran Taylor T. Johnson 88 292 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 1,838 0 03 Feb 2017