BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen - ECPv5.7.0//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
X-ORIGINAL-URL:https://www.greyc.fr
X-WR-CALDESC:évènements pour GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
BEGIN:VTIMEZONE
TZID:Europe/Paris
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20260329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20261025T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Paris:20260618T140000
DTEND;TZID=Europe/Paris:20260618T160000
DTSTAMP:20260615T145528
CREATED:20260605T085738Z
LAST-MODIFIED:20260605T085738Z
UID:12166-1781791200-1781798400@www.greyc.fr
SUMMARY:Séminaire Image: Balancing fidelity and interpretability in XAI for global model understanding and frugal AI design par Caroline Mazini Rodrigues
DESCRIPTION:Nous aurons le plaisir d’écouter Caroline Mazini Rodrigues\, Postdoctorante à l’IRISA (Rennes).\nElle donnera un séminaire IMAGE le jeudi 18 juin 2026 à 14h en salle de séminaire F-200 \nTitre: Balancing fidelity and interpretability in XAI for global model understanding and frugal AI design \nRésumé: \nAs neural networks grow in complexity\, understanding their decision-making processes has become important for ensuring transparency\, fairness\, and trustworthiness. Explainable Artificial Intelligence (XAI) addresses this challenge by identifying the features that influence model predictions. However\, highly faithful explanations are often difficult for humans to interpret\, while simpler explanations may fail to accurately reflect the model’s reasoning. This talk presents work on balancing the faithfulness-interpretability trade-off in post-hoc explanation methods\, with applications to bias understanding in vision models. We then explore another research direction at the intersection of XAI and Frugal AI\, examining how explanation-based insights can guide the design of more efficient and resource-aware AI models. This line of work positions interpretability not only as a diagnostic tool\, but as a mechanism for improving computational efficiency and responsible AI. \n 
URL:https://www.greyc.fr/event/seminaire-image-balancing-fidelity-and-interpretability-in-xai-for-global-model-understanding-and-frugal-ai-design-par-caroline-mazini-rodrigues/
LOCATION:ENSICAEN – Batiment F – Salle F-200\, 6 Bd Maréchal Juin\, Caen\, 14050\, France
CATEGORIES:General,Image,Seminaire Image
END:VEVENT
END:VCALENDAR