The Future of Learning-based Artificial Intelligence
EPFL Hub for Machine Learning Theory and Methodology with Applications
ML brings together EPFL faculty developing cross-cutting machine learning theory and methodology towards artificial intelligence systems for key engineering, scientific, and societal applications.
From undergrades to PhDs, EPFL has plenty of Machine Learning courses to offer.
Research is a major part in the Machine Learning field. With publications at premiere ML venues each year, EPFL has a strong standing.
You can find exciting ML related events and news from EPFL here.
EPFL papers @ AISTATS 2022
The following EPFL papers have been accepted to AISTATS 2022 (25th International Conference on Artificial Intelligence and Statistics). The conference will be held virtually from March 28-30, 2022.
EPFL papers @ ICLR 2022
The following EPFL papers have been accepted to ICLR 2022 (10th International Conference on Learning Representations). The conference will be held virtually from April 25-29,2022.
"Machine learning in chemistry and beyond" (ChE-651) seminar by Simon Batzner "Equivariant Interatomic Potentials"
With: Simon is a PhD student in Applied Mathematics at Harvard. While interested in far too many things for his own good, his research focuses on building deep learning systems for applications in computational physics and chemistry. Before joining Harvard, he worked on machine learning at MIT and on the NASA mission SOFIA. In his free time, you can find him playing soccer, hiking, and swimming. He comes to Harvard having finished his Master’s at MIT. He is originally from beautiful Illertissen, Germany.
Category: Conferences – Seminars