An Adaptive Parallel SAT Solver. - Gilles Audemard; Jean-Marie Lagniez; Nicolas Szczepanski; Sébastien Tabary (CP, 2016)

A Distributed Version of Syrup. - Gilles Audemard; Jean-Marie Lagniez; Nicolas Szczepanski; Sébastien Tabary (SAT, 2017)

SAT en Parallèle. (SAT Parallel Computing). - Nicolas Szczepanski (2017)

DMC: A Distributed Model Counter. - Jean-Marie Lagniez; Pierre Marquis; Nicolas Szczepanski (IJCAI, 2018)

An Incremental SAT-Based Approach to the Graph Colouring Problem. - Gael Glorian; Jean-Marie Lagniez; Valentin Montmirail; Nicolas Szczepanski (CP, 2019)

Multi-objective Automatic Algorithm Configuration for the Classification Problem of Imbalanced Data. - Sara Tari; Nicolas Szczepanski; Lucien Mousin; Julie Jacques; Marie-Eléonore Kessaci; Laetitia Jourdan (CEC, 2020)

Automatic Configuration of Multi-Thread Local Search: Preliminary Results on Bi-objective TSP. - Nicolas Szczepanski; Lucien Mousin; Nadarajen Veerapen; Laetitia Jourdan (ICTAI, 2020)

PYCSP3: Modeling Combinatorial Constrained Problems in Python. - Christophe Lecoutre; Nicolas Szczepanski (CoRR, 2020)

A hybrid CP/MOLS approach for multi-objective imbalanced classification. - Nicolas Szczepanski; Gilles Audemard; Laetitia Jourdan; Christophe Lecoutre; Lucien Mousin; Nadarajen Veerapen (GECCO, 2021)

Computing Abductive Explanations for Boosted Trees. - Gilles Audemard; Jean-Marie Lagniez; Pierre Marquis; Nicolas Szczepanski (AISTATS, 2023)

On Contrastive Explanations for Tree-Based Classifiers. - Gilles Audemard; Jean-Marie Lagniez; Pierre Marquis; Nicolas Szczepanski (ECAI, 2023)

PyXAI : calculer en Python des explications pour des modèles d'apprentissage supervisé. - Gilles Audemard; Steve Bellart; Louenas Bounia; Jean-Marie Lagniez; Pierre Marquis; Nicolas Szczepanski (EGC, 2023)

Designing an XAI Interface for Tree-Based ML Models. - Gilles Audemard; Sylvie Coste-Marquis; Pierre Marquis; Mehdi Sabiri; Nicolas Szczepanski (ECAI, 2024)

On the Computation of Example-Based Abductive Explanations for Random Forests. - Gilles Audemard; Jean-Marie Lagniez; Pierre Marquis; Nicolas Szczepanski (IJCAI, 2024)

Deriving Provably Correct Explanations for Decision Trees: The Impact of Domain Theories. - Gilles Audemard; Jean-Marie Lagniez; Pierre Marquis; Nicolas Szczepanski (IJCAI, 2024)

PyXAI: An XAI Library for Tree-Based Models. - Gilles Audemard; Jean-Marie Lagniez; Pierre Marquis; Nicolas Szczepanski (IJCAI, 2024)

Une interface XAI pour des modèles d'apprentissage automatique à base d'arbres. - Gilles Audemard; Sylvie Coste-Marquis; Pierre Marquis; Mehdi Sabiri; Nicolas Szczepanski (EGC, 2025)