Michael Galkin

Michael Galkin

Graph ML, GNNs, Geometric DL, Knowledge Graphs

Representation Learning on RDF* and LPG Graphs

less than 1 minute read

Published:

I wrote a new Medium post about our recent EMNLP 2020 paper “Message Passing for Hyper-Relational Knowledge Graphs” where we design graph neural nets for more complex graph structures such as hyper-relational KGs like Wikidata.

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Graph Learning Tutorial @ ICML 2024

Published: | less than 1 minute read

Participated (online) in the panel discussion with Bryan Perozzi, Michael Bronstein, and Christopher Morris on graph foundation models held during the Graph Learning Tutorial at ICML 2024, thanks Ameya and Adrian for inviting!

Foundation Models in Graph & Geometric Deep Learning

Published: | less than 1 minute read

In our new Medium blogpost with Michael Bronstein, Jianan Zhao, Haitao Mao, and Zhaocheng Zhu we discuss foundation models in Graph & Geometric DL: from the core theoretical and data challenges to the most recent models that you can try already today!