Robust Explainable AI
Author:   Francesco Leofante ,  Matthew Wicker
Publisher:   Springer International Publishing AG
ISBN:  

9783031890215


Pages:   71
Publication Date:   25 May 2025
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Robust Explainable AI


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Full Product Details

Author:   Francesco Leofante ,  Matthew Wicker
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
ISBN:  

9783031890215


ISBN 10:   3031890213
Pages:   71
Publication Date:   25 May 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Foreword.- Preface.- Acknowledgements.- 1. Introduction.- 2. Explainability in Machine Learning: Preliminaries & Overview.- 3. Robustness of Counterfactual Explanations.- 4. Robustness of Saliency-Based Explanations.

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Author Information

Francesco Leofante is a researcher affiliated with the Centre for Explainable AI at Imperial College. His research focuses on explainable AI, with special emphasis on counterfactual explanations for AI-based decision-making. His recent work highlighted several vulnerabilities of counterfactual explanations and proposed innovative solutions to improve their robustness. Matthew Wicker is an Assistant Professor (Lecturer) at Imperial College London and a Research Associate at The Alan Turing Institute. He works on formal verification of trustworthy machine learning properties with collaborators form academia and industry. His work focuses on provable guarantees for diverse notions of trustworthiness for machine learning models in order to enable responsible deployment.

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