Our research group is part of the School of Computer and Communication Sciences at EPFL in Lausanne, Switzerland. The group is lead by Matthias Grossglauser and Patrick Thiran. Our research focuses broadly on the statistical modeling of large dynamical systems involving both human and technical agents. Examples include social and information networks, epidemic processes, human mobility and transportation, and recommender systems. Our work lies at the intersection of machine learning, probabilistic modeling, large-scale data analytics, and performance analysis. Here are the research areas we work on:
Generalization Comparison of Deep Neural Networks via Output Sensitivity M. Forouzesh, F. Salehi and P. Thiran 25th International Conference on Pattern Recognition, Milan, Italy, January 10-15, 2021.
War of Words II: Enriched Models of Law-Making Processes V. Kristof, A. Suresh, M. Grossglauser and P. Thiran The Web Conference 2021 (WWW '21), Ljubljana, Slovenia, April 19-23, 2021.
A Variational Inference Approach to Learning Multivariate Wold Processes J. Etesami, W. Trouleau, N. Kiyavash, M. Grossglauser and P. Thiran 24th International Conference on Artificial Intelligence and Statistics (AISTATS), San Diego, California, USA, April 13-15, 2021.
Metric dimension of critical Galton–Watson trees and linear preferential attachment trees J. Komjáthy and G. Ódor European Journal of Combinatorics, 2021.
A meta-learning approach for genomic survival analysis Y. L. Qiu, H. Zheng, A. Devos, H. Selby and O. Gevaert Nature Communications, 2020.