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HES-XPLAIN - an open platform for accelerating the development of eXplainable AI systems

Babey, Arthur; Boutay, Jean-Marc; Marquis, Rémy; Costa, Damian Boquete; Bologna, Guido; Graf, Marcel; Brochet, Xavier; Peña-Reyes, Carlos Andrés
2025
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Abstract

AI is widely adopted, but users often struggle to trust decisions they don’t understand. Explainable AI (XAI) aims to address this issue, yet many tools remain complex. HES-XPLAIN, our open-source platform, simplifies access to XAI with intuitive methods and support for diverse data types. It includes a comprehensive library, notebooks, and documentation, designed for data scientists, decision-makers, educators, and others to help them integrate XAI in their AI projects.

Details

Title
HES-XPLAIN - an open platform for accelerating the development of eXplainable AI systems
Author(s)
Babey, Arthur (School of Engineering and Management Vaud, HES-SO University of Applied Sciences and Arts Western Switzerland)
Boutay, Jean-Marc (School of Engineering, Architecture and Landscape (HEPIA), HES-SO // University of Applied Sciences and Arts Western Switzerland)
Marquis, Rémy (School of Engineering and Management Vaud, HES-SO University of Applied Sciences and Arts Western Switzerland)
Costa, Damian Boquete (School of Engineering, Architecture and Landscape (HEPIA), HES-SO // University of Applied Sciences and Arts Western Switzerland)
Bologna, Guido (School of Engineering, Architecture and Landscape (HEPIA), HES-SO // University of Applied Sciences and Arts Western Switzerland)
Graf, Marcel (School of Engineering and Management Vaud, HES-SO University of Applied Sciences and Arts Western Switzerland)
Brochet, Xavier (School of Engineering and Management Vaud, HES-SO University of Applied Sciences and Arts Western Switzerland)
Peña-Reyes, Carlos Andrés (School of Engineering and Management Vaud, HES-SO University of Applied Sciences and Arts Western Switzerland)
Date
2025-01
Published in
AI days HES-SO '25
Volume
2025
Pagination & equivalents
7 p.
Presented at
AI days HES-SO '25, Geneva, Switzerland, 2025-01-27, 2025-01-29
Keywords
XAI ; explainability ; interpretability ; artificial intelligence
Paper type
conference proceedings
Faculty
Ingénierie et Architecture
School
HEPIA - Genève
HEIG-VD
Institute
IICT - Institut des Technologies de l'Information et de la Communication
inTECH - Institut d’ingénierie industrielle et informatique
Record Appears in
Conference materials
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