Ecole: A Gym-like Library for Machine Learning in Combinatorial Optimization Solvers. - Antoine Prouvost; Justin Dumouchelle; Lara Scavuzzo; Maxime Gasse; Didier Chételat; Andrea Lodi 001 (CoRR, 2020)

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. - Maxime Gasse; Simon Bowly; Quentin Cappart; Jonas Charfreitag; Laurent Charlin; Didier Chételat; Antonia Chmiela; Justin Dumouchelle; Ambros M. Gleixner; Aleksandr M. Kazachkov; Elias B. Khalil; Pawel Lichocki; et al. (NeurIPS (Competition and Demos), 2021)

Learning to Branch with Tree MDPs. - Lara Scavuzzo; Feng Yang Chen; Didier Chételat; Maxime Gasse; Andrea Lodi 001; Neil Yorke-Smith; Karen I. Aardal (NeurIPS, 2022)

The Machine Learning for Combinatorial Optimization Competition (ML4CO): Results and Insights. - Maxime Gasse; Quentin Cappart; Jonas Charfreitag; Laurent Charlin; Didier Chételat; Antonia Chmiela; Justin Dumouchelle; Ambros M. Gleixner; Aleksandr M. Kazachkov; Elias B. Khalil; Pawel Lichocki; Andrea Lodi 001; et al. (CoRR, 2022)

Optimal entanglement distribution policies in homogeneous repeater chains with cutoffs. - Álvaro G. Iñesta; Gayane Vardoyan; Lara Scavuzzo; Stephanie Wehner (CoRR, 2022)

A study of lattice reformulations for integer programming. - Karen I. Aardal; Lara Scavuzzo; Laurence A. Wolsey (Oper. Res. Lett., 2023)

Machine Learning Augmented Branch and Bound for Mixed Integer Linear Programming. - Lara Scavuzzo; Karen I. Aardal; Andrea Lodi 001; Neil Yorke-Smith (CoRR, 2024)

Learning optimal objective values for MILP. - Lara Scavuzzo; Karen I. Aardal; Neil Yorke-Smith (CoRR, 2024)