Michael Bronstein's Blog
Michael BronsteinGeometric Deep Learning
| Platform |  | Pricing | Only free issues | Publishes | Monthly |
|---|---|---|---|---|---|
| Issues | 10 | Subscribers | Read | michaelbronstein.substack.com |
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Latest Issues
Recent posts by this newsletter. Browse the email archive.
Using subgraphs for more expressive GNNs
GNNs have limited expressive power due to their equivalence to WL test. Recent works show how to improve expressivity by using subgraphs.
Over-squashing, Bottlenecks, and Graph Ricci curvature
A concept from differential geometry called Ricci curvature allows to understand the phenomena of over-squashing and bottlenecks in GNNs
Graph Neural Networks through the lens of Differential Geometry and Algebraic Topology
New perspectives on old problems in Graph ML
Graph Neural Networks as Neural Diffusion PDEs
Graph neural networks are intimately related to partial differential equations governing information diffusion on graphs.
Authors
The writers behind this newsletter.
Professor @ImperialCollege @USI_en / Head of Graph ML @Twitter / ML Lead @ProjectCETI / ex Founder & Chief Scientist @Fabula_ai / ex @Intel #AI #ML #graphs
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