Learning Classification with Both Labeled and Unlabeled Data. - Jean-Noël Vittaut; Massih-Reza Amini; Patrick Gallinari (ECML, 2002)

Structured multimedia document classification. - Ludovic Denoyer; Jean-Noël Vittaut; Patrick Gallinari; Sylvie Brunessaux; Stephan Brunessaux (ACM Symposium on Document Engineering, 2003)

An Algebra for Structured Queries in Bayesian Networks. - Jean-Noël Vittaut; Benjamin Piwowarski; Patrick Gallinari (INEX, 2004)

Machine Learning Ranking and INEX'05. - Jean-Noël Vittaut; Patrick Gallinari (INEX, 2005)

Apprentissage d'ordonnancements en recherche d'information structurée. - Patrick Gallinari; Jean-Noël Vittaut (CORIA, 2006)

Machine Learning Ranking for Structured Information Retrieval. - Jean-Noël Vittaut; Patrick Gallinari (ECIR, 2006)

Supervised and Semi-supervised Machine Learning Ranking. - Jean-Noël Vittaut; Patrick Gallinari (INEX, 2006)

Segmented Images Colorization Using Harmony. - Catherine Sauvaget; Stéphane Manuel; Jean-Noël Vittaut; Jordane Suarez; Vincent Boyer 001 (SITIS, 2010)

Automated Colorization of Segmented Images Based on Color Harmony. - Catherine Sauvaget; Jean-Noël Vittaut; Jordane Suarez; Vincent Boyer 001; Stéphane Manuel (J. Multim. Process. Technol., 2010)

Fast Instantiation of GGP Game Descriptions Using Prolog with Tabling. - Jean-Noël Vittaut; Jean Méhat (ECAI, 2014)

Efficient Grounding of Game Descriptions with Tabling. - Jean-Noël Vittaut; Jean Méhat (CGW@ECAI, 2014)

A General Approach of Game Description Decomposition for General Game Playing. - Aline Hufschmitt; Jean-Noël Vittaut; Jean Méhat (CGW@IJCAI, 2016)

Statistical GGP Game Decomposition. - Aline Hufschmitt; Jean-Noël Vittaut; Nicolas Jouandeau (CGW@IJCAI, 2018)

Exploiting Game Decompositions in Monte Carlo Tree Search. - Aline Hufschmitt; Jean-Noël Vittaut; Nicolas Jouandeau (ACG, 2019)

Operator Learning with Neural Fields: Tackling PDEs on General Geometries. - Louis Serrano; Lise Le Boudec; Armand Kassaï Koupaï; Thomas X. Wang; Yuan Yin; Jean-Noël Vittaut; Patrick Gallinari (NeurIPS, 2023)

TIGTEC: Token Importance Guided TExt Counterfactuals. - Milan Bhan; Jean-Noël Vittaut; Nicolas Chesneau; Marie-Jeanne Lesot (ECML/PKDD (3), 2023)

Self-AMPLIFY: Improving Small Language Models with Self Post Hoc Explanations. - Milan Bhan; Jean-Noël Vittaut; Nicolas Chesneau; Marie-Jeanne Lesot (EMNLP, 2024)

Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning. - Armand Kassaï Koupaï; Jorge Mifsut Benet; Yuan Yin; Jean-Noël Vittaut; Patrick Gallinari (NeurIPS, 2024)

AROMA: Preserving Spatial Structure for Latent PDE Modeling with Local Neural Fields. - Louis Serrano; Thomas X. Wang; Etienne Le Naour; Jean-Noël Vittaut; Patrick Gallinari (NeurIPS, 2024)

Mitigating Text Toxicity with Counterfactual Generation. - Milan Bhan; Jean-Noël Vittaut; Nina Achache; Victor Legrand; Nicolas Chesneau; Annabelle Blangero; Juliette Murris; Marie-Jeanne Lesot (CoRR, 2024)

GEPS: Boosting Generalization in Parametric PDE Neural Solvers through Adaptive Conditioning. - Armand Kassaï Koupaï; Jorge Mifsut Benet; Yuan Yin; Jean-Noël Vittaut; Patrick Gallinari (CoRR, 2024)

Towards Achieving Concept Completeness for Unsupervised Textual Concept Bottleneck Models. - Milan Bhan; Yann Choho; Pierre Moreau; Jean-Noël Vittaut; Nicolas Chesneau; Marie-Jeanne Lesot (CoRR, 2025)

Did I Faithfully Say What I Thought? Bridging the Gap Between Neural Activity and Self-Explanations in Large Language Models. - Milan Bhan; Jean-Noël Vittaut; Nicolas Chesneau; Sarath Chandar; Marie-Jeanne Lesot (CoRR, 2025)