Gaël Letarte

After an integrated bachelor's degree in mathematics and computer science, Gaël began graduate studies in machine learning. His PhD research focused on the use of PAC-Bayesian theory for learning representations. During his studies, he became interested and published in various subfields, including bioinformatics, natural language processing and machine learning theory. His latest work proposing statistical guarantees for binary activated neural networks has been published at the prestigious international conference Neural Information Processing Systems (NeurIPS).