Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems

11 May 2018

Papers citing "Quantitative Projection Coverage for Testing ML-enabled Autonomous Systems"

10 / 10 papers shown

Title
A Survey of Neural Network Robustness Assessment in Image Recognition Jie Wang Jun Ai Minyan Lu Haoran Su Dan Yu Yutao Zhang Junda Zhu Jingyu Liu AAML 120 3 0 12 Apr 2024
Machine Learning with Requirements: a Manifesto Eleonora Giunchiglia F. Imrie M. Schaar Thomas Lukasiewicz AI4TS OffRL VLM 71 7 0 07 Apr 2023
Backdoor Mitigation in Deep Neural Networks via Strategic Retraining Akshay Dhonthi E. M. Hahn Vahid Hashemi AAML 47 2 0 14 Dec 2022
Prioritizing Corners in OoD Detectors via Symbolic String Manipulation Chih-Hong Cheng Changshun Wu Emmanouil Seferis Saddek Bensalem 130 3 0 16 May 2022
Unaligned but Safe -- Formally Compensating Performance Limitations for Imprecise 2D Object Detection Tobias Schuster Emmanouil Seferis Simon Burton Chih-Hong Cheng 63 6 0 10 Feb 2022
Towards Robust Direct Perception Networks for Automated Driving Chih-Hong Cheng 19 1 0 30 Sep 2019
A Systematic Mapping Study on Testing of Machine Learning Programs S. Sherin Muhammad Uzair Khan Muhammad Zohaib Z. Iqbal 39 13 0 11 Jul 2019
A Survey of Safety and Trustworthiness of Deep Neural Networks: Verification, Testing, Adversarial Attack and Defence, and Interpretability Xiaowei Huang Daniel Kroening Wenjie Ruan Marta Kwiatkowska Youcheng Sun Emese Thamo Min Wu Xinping Yi AAML 130 51 0 18 Dec 2018
Towards Dependability Metrics for Neural Networks Chih-Hong Cheng Georg Nührenberg Chung-Hao Huang Harald Ruess Hirotoshi Yasuoka 75 44 0 06 Jun 2018
Testing Deep Neural Networks Youcheng Sun Xiaowei Huang Daniel Kroening James Sharp Matthew Hill Rob Ashmore AAML 88 219 0 10 Mar 2018