Geometric Deep Learning

Topic | v1 | created by jjones |

Geometric Deep Learning is an attempt for geometric unification of a broad class of ML problems from the perspectives of symmetry and invariance. These principles not only underlie the breakthrough performance of convolutional neural networks and the recent success of graph neural networks but also provide a principled way to construct new types of problem-specific inductive biases.


subtopic of Deep learning

Deep learning (also known as deep structured learning) is part of a broader family of machine learnin...

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treated in #60 Geometric Deep Learning Blueprint (Special Edition)

This week we spoke with Professor Michael Bronstein (head of graph ML at Twitter) and Dr. Petar Vel...