Reading group in theoretical deep learning

This is the main page of the reading group in theoretical deep learning coorganised by Manuel Lecha Sánchez and Rubén Ballester Bautista. We meet each two weeks at Universitat de Barcelona to discuss relevant topics in theoretical deep learning from a mathematic point of view.

Forthcoming sessions

Introduction to neural networks

Associated article: Generalization in Deep Learning
Authors: Kenji Kawaguchi, Leslie Pack Kaelbling, Yoshua Bengio
Speaker: Rubén Ballester Bautista
Date: 20/04/2023

Geometric priors on Deep Weight spaces

Associated article: Equivariant Architectures for Learning in Deep Weight Spaces
Authors: Aviv Navon, Aviv Shamsian, Idan Achituve, Ethan Fetaya, Gal Chechik, Haggai Maron
Speaker: Manuel Lecha Sánchez
Date: 04/05/2023

Previous sessions

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