Anticipating epidemic transitions with imperfect data. - Tobias S. Brett; Eamon B. O'Dea; Éric Marty; Paige B. Miller; Andrew W. Park; John M. Drake; Pejman Rohani (PLoS Comput. Biol., 2018)

The statistics of epidemic transitions. - John M. Drake; Tobias S. Brett; Shiyang Chen 008; Bogdan I. Epureanu; Matthew J. Ferrari; Éric Marty; Paige B. Miller; Eamon B. O'Dea; Suzanne M. O'Regan; Andrew W. Park; Pejman Rohani (PLoS Comput. Biol., 2019)

AIM 2020 Challenge on Efficient Super-Resolution: Methods and Results. - Kai Zhang 008; Martin Danelljan; Yawei Li 001; Radu Timofte; Jie Liu 040; Jie Tang 006; Gangshan Wu; Yu Zhu 004; Xiangyu He; Wenjie Xu; Chenghua Li; Cong Leng; et al. (ECCV Workshops (3), 2020)

Reducing P4 language's voluminosity using higher-level constructs. - Albert Gran Alcoz; Coralie Busse-Grawitz; Éric Marty; Laurent Vanbever (EuroP4@CoNEXT, 2022)

A data-driven semi-parametric model of SARS-CoV-2 transmission in the United States. - John M. Drake; Andreas Handel; Éric Marty; Eamon B. O'Dea; Tierney O'Sullivan; Giovanni Righi; Andrew T. Tredennick (PLoS Comput. Biol., 2023)

Physics-informed deep learning for infectious disease forecasting. - Ying Qian; Éric Marty; Avranil Basu; Eamon B. O'Dea; Xianqiao Wang; Spencer Fox; Pejman Rohani; John M. Drake; He Li (CoRR, 2025)