Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)

2 February 2021

Papers citing "Guidance on the Assurance of Machine Learning in Autonomous Systems (AMLAS)"

33 / 33 papers shown

Title
A Guide to Failure in Machine Learning: Reliability and Robustness from Foundations to Practice Eric Heim Oren Wright David Shriver OOD FaML 73 0 0 01 Mar 2025
Landscape of AI safety concerns - A methodology to support safety assurance for AI-based autonomous systems Ronald Schnitzer Lennart Kilian Simon Roessner Konstantinos Theodorou Sonja Zillner 89 0 0 18 Dec 2024
Developing Assurance Cases for Adversarial Robustness and Regulatory Compliance in LLMs Tomas Bueno Momcilovic Dian Balta Beat Buesser Giulio Zizzo Mark Purcell AAML 30 0 0 04 Oct 2024
A SAT-based approach to rigorous verification of Bayesian networks Yang Luo Zhemeng Yu Lintao Ma 39 0 0 02 Aug 2024
Learning Run-time Safety Monitors for Machine Learning Components Ozan Vardal Richard Hawkins Colin Paterson Chiara Picardi Daniel Omeiza Lars Kunze Ibrahim Habli 38 0 0 23 Jun 2024
The Open Autonomy Safety Case Framework Michael Wagner Carmen Carlan ELM 18 2 0 08 Apr 2024
What's my role? Modelling responsibility for AI-based safety-critical systems Philippa Ryan Zoe Porter Joanna Al-Qaddoumi John McDermid Ibrahim Habli 34 1 0 30 Dec 2023
Operationalizing Assurance Cases for Data Scientists: A Showcase of Concepts and Tooling in the Context of Test Data Quality for Machine Learning Lisa Jöckel Michael Kläs Janek Groß Pascal Gerber Markus Scholz ... Marc Teschner Daniel Seifert Richard Hawkins John Molloy Jens Ottnad 19 0 0 08 Dec 2023
KnowSafe: Combined Knowledge and Data Driven Hazard Mitigation in Artificial Pancreas Systems Xugui Zhou Maxfield Kouzel Chloe Smith H. Alemzadeh 27 1 0 13 Nov 2023
AI Hazard Management: A framework for the systematic management of root causes for AI risks Ronald Schnitzer Andreas Hapfelmeier Sven Gaube Sonja Zillner 24 3 0 25 Oct 2023
Towards a safe MLOps Process for the Continuous Development and Safety Assurance of ML-based Systems in the Railway Domain M. Zeller T. Waschulzik Reiner N. Schmid Claus Bahlmann 20 3 0 06 Jul 2023
Assurance for Autonomy -- JPL's past research, lessons learned, and future directions M. Feather A. Pinto 11 1 0 16 May 2023
Assessing Trustworthiness of Autonomous Systems Greg Chance Dhaminda B. Abeywickrama Beckett LeClair Owen Kerr Kerstin Eder 13 5 0 05 May 2023
AERoS: Assurance of Emergent Behaviour in Autonomous Robotic Swarms Dhaminda B. Abeywickrama James Wilson Suet Lee Greg Chance Peter D. Winter Arianna Manzini Ibrahim Habli Shane Windsor Sabine Hauert Kerstin Eder 27 5 0 20 Feb 2023
A Trustworthiness Score to Evaluate DNN Predictions Abanoub Ghobrial Darryl Hond Hamid Asgari Kerstin Eder 27 2 0 21 Jan 2023
Towards Developing Safety Assurance Cases for Learning-Enabled Medical Cyber-Physical Systems Maryam Bagheri Josephine Lamp Xugui Zhou Lu Feng H. Alemzadeh 16 4 0 23 Nov 2022
Creating a Safety Assurance Case for an ML Satellite-Based Wildfire Detection and Alert System Richard Hawkins Chiara Picardi Lucy Donnell Murray L. Ireland 12 2 0 08 Nov 2022
Review of the AMLAS Methodology for Application in Healthcare Shakir Laher Carla Brackstone S. Reis An Nguyen Sean White Ibrahim Habli 14 2 0 01 Sep 2022
Safety Assessment for Autonomous Systems' Perception Capabilities J. Molloy John McDermid 32 4 0 17 Aug 2022
Model predictivity assessment: incremental test-set selection and accuracy evaluation E. Fekhari Bertrand Iooss Joseph Muré L. Pronzato M. Rendas 23 13 0 08 Jul 2022
Evaluating Automated Driving Planner Robustness against Adversarial Influence Andres Molina-Markham Silvia G. Ionescu Erin Lanus Derek Ng Sam Sommerer J. Rushanan AAML 29 0 0 29 May 2022
Ergo, SMIRK is Safe: A Safety Case for a Machine Learning Component in a Pedestrian Automatic Emergency Brake System Markus Borg Jens Henriksson Kasper Socha Olof Lennartsson Elias Sonnsjo Lonegren T. Bui Piotr Tomaszewski S. Sathyamoorthy Sebastian Brink M. H. Moghadam 35 23 0 16 Apr 2022
A Principles-based Ethics Assurance Argument Pattern for AI and Autonomous Systems Zoe Porter Ibrahim Habli John McDermid Marten H. L. Kaas 6 14 0 29 Mar 2022
Machine Learning Testing in an ADAS Case Study Using Simulation-Integrated Bio-Inspired Search-Based Testing M. H. Moghadam Markus Borg Mehrdad Saadatmand Seyed Jalaleddin Mousavirad M. Bohlin B. Lisper 22 10 0 22 Mar 2022
Safe AI -- How is this Possible? Harald Ruess Simon Burton 29 0 0 25 Jan 2022
The Role of Explainability in Assuring Safety of Machine Learning in Healthcare Yan Jia John McDermid T. Lawton Ibrahim Habli 33 48 0 01 Sep 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 26 31 0 09 Jun 2021
Sample selection from a given dataset to validate machine learning models Bertrand Iooss 13 2 0 27 Apr 2021
An NCAP-like Safety Indicator for Self-Driving Cars Jim Huang H. Kurniawati 12 1 0 02 Apr 2021
DeepSafe: A Data-driven Approach for Checking Adversarial Robustness in Neural Networks D. Gopinath Guy Katz C. Păsăreanu Clark W. Barrett AAML 50 87 0 02 Oct 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 257 3,696 0 28 Feb 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
Safety Verification of Deep Neural Networks Xiaowei Huang Marta Kwiatkowska Sen Wang Min Wu AAML 183 932 0 21 Oct 2016