LOGML - Thomas Kipf: Relational Structure Discovery
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LOGML 2021: Intro session + Michael Bronstein: Geometric Deep Learning: from Euclid to Drug Design
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LOGML - Niloy Mitra: Deep 3D Generative Modeling
LOGML - Maks Ovsjanikov: Robust learning-based methods for shape correspondence
Keynote: Computational Topology and Applications to Biological Data (Prof. Heather Harrington)
LOGML + WiC Tutorial: Getting started on graph ML
LOGML - Marinka Zitnik: Graph Representation Learning for Biomedical Discovery
LOGML - Martin Rumpf
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LOGML - Sanja Fidler
LOGML 2022 IS COMING!
Type-checking Graph Neural Networks (Dr. Petar Veličković)
LOGML - Gabriele Steidl
Tutorial: PyTorch Geometric (Jianxuan You, Rex Ying)
Tutorial: Topological Data Analysis (Katherine Benjamin)
LOGML - Smita Krishnaswamy
Fisher Information Geometry of Beta and Dirichlet Distributions (Dr. Alice Le Brigant)
From Equivariance to Naturality (Dr. Taco Cohen)
LOGML - Michael Betancourt: Unravelling A Geometric Conspiracy
Universes as Big-Data: Physics, Geometry & AI (Prof. Yang-Hui He)