For further info about Statify team members, please visit the members' page.
Kostas Pitas (2022-2024), Inria. PAC-Bayesian generalization bounds.
Julien Zhou (2022-) Inria-Criteo, co-advised with Pierre Gaillard and Thibaud Rahier.
Louise Alamichel (2021) Université Paris-Saclay, Orsay, co-advised with Daria Bystrova and Guillaume Kon Kam King. Asymptotic properties of Bayesian nonparametric mixture models.
Tony Zhang (2020) Trinity College Dublin, co-advised with Stéphane Girard. Bayesian extreme value models.
Sharan Yalburgi (2019) Birla Institute of Technology and Science, India (BITS). Bayesian deep learning for model selection and approximate inference.
Fatoumata Dama (2019) Université Grenoble-Alpes, co-advised with Jean-Baptiste Durand and Florence Forbes, Bayesian nonparametric models for hidden Markov random fields on count variables and application to disease mapping.
Caroline Lawless (2018) Trinity College Dublin. An elementary derivation of the Chinese restaurant process from the stick-breaking representation for the Pitman--Yor process.
Aleksandra Malkova (2018) Université Grenoble-Alpes, co-advised with Maria Laura Delle Monache. DATASAFE: understanding Data Accidents for TrAffic SAFEty.
Michal Lewandowski (2018) Université Grenoble-Alpes. Theoretical properties of Bayesian nonparametric clustering.
Cecilia Ferrando (2016) Collegio Carlo Alberto, Moncalieri, Italy. Bayesian stochastic blockmodels.