Visits Visit of Lena Stempfle from Chalmers University of Technology from 22 April to 22 May Visit of Shu Yang from North Carolina University from 17 to 23 May Talks 22 April : Sven Klaaßen. DoubleMLDeep: Estimation of Causal Effects with Multimodal Data 29 April : Lena Stempfle. Interpretable machine…
Julie Josse is invited to give a talk at the European Conference on Causal Inference and Jeffrey Näf presents Causal Distributional Random Forest.
Krystyna Grzesiak from University of Wroclaw and Michal Burdukiewicz from Autonomous University of Barcelona are both visiting the team in the upcoming days.
Large part of the team attended the great conference in Lisbon to give talks and we also organized a session on missing values.
The Digital Health PEPR , launched in June 2023 as part of the Health Innovation Plan 2030, is a major initiative in the “Digital Health” acceleration strategy with a programme dedicated to stimulating scientific research in this field. SMATCH “Statistical and AI Methods for the Challenges of Modern Clinical Trials…
We organized a day between Premedical thesis students and students of Raphael Porcher and François Petit from the cress Methods team on causal inference methods.
For two days we gathered to test the machine learning methods that will be implemented in a decision support tool for major trauma care. A clinical trial will be launched to test the tool in sixteen dispatch centers in France. It is supposed to improve the triage of major trauma…
This award rewards her PhD thesis on probabilistic forecasting (conformal prediction). This is a way to encourage women in science. Read her interview!
by Margaux Zaffran: https://mzaffran.github.io/assets/files/Talks/Tuto_CP_ENBIS_ECAS.pdf
Aurélien Bellet, a “Directeur de Recherche” at Inria, leader in the field of Federated Learning is joining PreMeDiCal at the begining of August 2023. The team is extremely pleased to welcome him. Besides Federated Learning, Aurélien also works on privacy and fairness in machine learning, and more generally optimization for…
