VITTAUT Jean-Noël
Associate Professor
Team : LFI
Tel: +33 1 44 27 88 03, Jean-Noel.Vittaut (at) nulllip6.fr
https://webia.lip6.fr/~vittaut/
Team : LFI
- Sorbonne Université - LIP6
Boîte courrier 169
Couloir 26-00, Étage 5, Bureau 512
4 place Jussieu
75252 PARIS CEDEX 05
FRANCE
Tel: +33 1 44 27 88 03, Jean-Noel.Vittaut (at) nulllip6.fr
https://webia.lip6.fr/~vittaut/
Two PhD students at Sorbonne University (Supervision / Co-supervision)
- BHAN Milan : Generation of counterfactual texts.
- TALBI Feryal : L'intelligence artificielle au service des géosciences : entrelacement des graphes de connaissances et de l'apprentissage automatique pour décrypter les processus terrestres.
2002-2024 Publications
-
2024
- A. Koupaï, J. Benet, Y. Yin, J.‑N. Vittaut, P. Gallinari : “GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning”, Advances in Neural Information Processing Systems, Vancouver, Canada (2024)
-
2023
- L. Serrano, L. Boudec, A. Koupaï, Th. Wang, Y. Yin, J.‑N. Vittaut, P. Gallinari : “Operator Learning with Neural Fields: Tackling PDEs on General Geometries”, Advances in Neural Information Processing Systems, vol. 36, New Orleans (Louisiana), United States, pp. 70581-70611 (2023)
- M. Bhan, J.‑N. Vittaut, N. Chesneau, M.‑J. Lesot : “TIGTEC : Token Importance Guided TExt Counterfactuals”, Machine Learning and Knowledge Discovery in Databases: Research Track. ECML PKDD 2023. Lecture Notes in Computer Science, vol. 14171 (3), Lecture Notes in Computer Science, Turin, Italy, pp. 496–512, (Springer), (ISBN: 978-3-031-43417-4) (2023)
- M. Bhan, J.‑N. Vittaut, N. Chesneau, M.‑J. Lesot : “Enhancing textual counterfactual explanation intelligibility through Counterfactual Feature Importance”, Proceedings of the 3rd Workshop on Trustworthy Natural Language Processing (TrustNLP 2023), Toronto, Canada, pp. 221-231, (Association for Computational Linguistics) (2023)
- L. Serrano, J.‑N. Vittaut, P. Gallinari : “Operator Learning on Free-Form Geometries”, ICLR 2023 Workshop on Physics for Machine Learning, Kigali, Rwanda (2023)
-
2022
- Ch. Marsala, I. Bloch, M.‑J. Lesot, S. Tollari, J.‑N. Vittaut : “Recherches en IA explicable dans l’équipe LFI du LIP6”, Bulletin de l'Association Française pour l'Intelligence Artificielle n°116, pp. 9-13, (AFIA) (2022)
-
2019
- A. Hufschmitt, J.‑N. Vittaut, N. Jouandeau : “Exploiting Game Decompositions in Monte Carlo Tree Search”, Proceedings of the 16th Advances in Computer Games Conference (ACG’19), Macao, China (2019)
-
2006
- J.‑N. Vittaut, P. Gallinari : “Supervised and Semi-supervised Machine Learning Ranking”, Advances in XML Information Retrieval and Evaluation: Fifth Workshop of the INitiative for the Evaluation of XML Retrieval (INEX'06), vol. 4518, Lecture Notes in Computer Science, Dagstuhl, Germany, pp. 213-222, (Springer) (2006)
- J.‑N. Vittaut, P. Gallinari : “Machine Learning Ranking for Structured Information Retrieval”, European Conference on Information Retrieval (ECIR 2006), vol. 3936, Lecture Notes in Computer Science, London, United Kingdom, pp. 338-349, (Springer) (2006)
- J.‑N. Vittaut, P. Gallinari : “Apprentissage d’ordonnancements en Recherche d’Information Structurée”, 3e Conference en Recherche d'Information et Applications (CORIA'06), Lyon, France, pp. 17-28 (2006)
-
2005
- J.‑N. Vittaut, P. Gallinari : “Machine Learning Ranking and INEX’05”, INEX 2005 - 4th Workshop of the INitiative for the Evaluation of XML Retrieval, vol. 3977, Lecture Notes in Computer Science, Dagstuhl, Germany, pp. 336-343, (Springer) (2005)
-
2004
- J.‑N. Vittaut, B. Piwowarski, P. Gallinari : “An Algebra for Structured Queries in Bayesian Networks”, 3rd Workshop of the INitiative for the Evaluation of XML Retrieval (INEX'04), vol. 3493, Lecture Notes in Computer Science, Dagstuhl, Germany, pp. 100-112, (Springer) (2004)
-
2003
- L. Denoyer, J.‑N. Vittaut, P. Gallinari, S. Brunessaux, S. Brunessaux : “Structured Multimedia Document Classification”, ACM Document Engeneering, Grenoble, France, pp. 153-160, (ACM) (2003)
-
2002
- J.‑N. Vittaut, M.‑R. Amini, P. Gallinari : “Learning Classification with Both Labeled and Unlabeled Data”, Machine Learning: ECML 2002, 13th European Conference on Machine Learning, vol. 2430, Lecture Notes in Computer Science, Helsinki, Finland, pp. 468-479, (Springer) (2002)