Assessing privacy and quality of synthetic health data. - Andrew Yale; Saloni Dash; Ritik Dutta; Isabelle Guyon; Adrien Pavao; Kristin P. Bennett (AIDR, 2019)

Privacy Preserving Synthetic Health Data. - Andrew Yale; Saloni Dash; Ritik Dutta; Isabelle Guyon; Adrien Pavao; Kristin P. Bennett (ESANN, 2019)

Towards Automated Deep Learning: Analysis of the AutoDL challenge series 2019. - Zhengying Liu; Zhen Xu 007; Shangeth Rajaa; Meysam Madadi; Júlio C. S. Jacques Júnior; Sergio Escalera; Adrien Pavao; Sébastien Treguer; Wei-Wei Tu; Isabelle Guyon (NeurIPS (Competition and Demos), 2019)

Synthetic Event Time Series Health Data Generation. - Saloni Dash; Ritik Dutta; Isabelle Guyon; Adrien Pavao; Andrew Yale; Kristin P. Bennett (CoRR, 2019)

Generation and evaluation of privacy preserving synthetic health data. - Andrew Yale; Saloni Dash; Ritik Dutta; Isabelle Guyon; Adrien Pavao; Kristin P. Bennett (Neurocomputing, 2020)

Towards automated computer vision: analysis of the AutoCV challenges 2019. - Zhengying Liu; Zhen Xu 007; Sergio Escalera; Isabelle Guyon; Júlio C. S. Jacques Júnior; Meysam Madadi; Adrien Pavao; Sébastien Treguer; Wei-Wei Tu (Pattern Recognit. Lett., 2020)

Judging competitions and benchmarks: a candidate election approach. - Adrien Pavao; Isabelle Guyon; Michael Vaccaro (ESANN, 2021)

Aircraft Numerical "Twin": A Time Series Regression Competition. - Adrien Pavao; Isabelle Guyon; Nachar Stéphane; Fabrice Lebeau; Martin Ghienne; Ludovic Platon; Tristan Barbagelata; Pierre Escamilla; Sana Mzali; Meng Liao; Sylvain Lassonde; Antonin Braun; et al. (ICMLA, 2021)

Winning Solutions and Post-Challenge Analyses of the ChaLearn AutoDL Challenge 2019. - Zhengying Liu; Adrien Pavao; Zhen Xu 007; Sergio Escalera; Fabio Ferreira; Isabelle Guyon; Sirui Hong; Frank Hutter; Rongrong Ji; Júlio C. S. Jacques Júnior; Ge Li; Marius Lindauer; et al. (IEEE Trans. Pattern Anal. Mach. Intell., 2021)

Filtering participants improves generalization in competitions and benchmarks. - Adrien Pavão; Isabelle Guyon; Zhengying Liu (ESANN, 2022)

Reinforcement learning for Energies of the future and carbon neutrality: a Challenge Design. - Gaëtan Serré; Eva Boguslawski; Benjamin Donnot; Adrien Pavão; Isabelle Guyon; Antoine Marot (CoRR, 2022)

Codabench: Flexible, easy-to-use, and reproducible meta-benchmark platform. - Zhen Xu 007; Sergio Escalera; Adrien Pavão; Magali Richard; Wei-Wei Tu; Quanming Yao; Huan Zhao 002; Isabelle Guyon (Patterns, 2022)

CodaLab Competitions: An Open Source Platform to Organize Scientific Challenges. - Adrien Pavao; Isabelle Guyon; Anne-Catherine Letournel; Dinh-Tuan Tran; Xavier Baró; Hugo Jair Escalante; Sergio Escalera; Tyler Thomas; Zhen Xu 007 (J. Mach. Learn. Res., 2023)

Methodology for Design and Analysis of Machine Learning Competitions. (Méthodologie pour la conception et l'analyse de compétitions en apprentissage automatique). - Adrien Pavão (2023)

AI Competitions and Benchmarks, Practical issues: Proposals, grant money, sponsors, prizes, dissemination, publicity. - Magali Richard; Yuna Blum; Justin Guinney; Gustavo Stolovitzky; Adrien Pavão (CoRR, 2024)