Towards Foundation Models for Graph Reasoning, M. Galkin, TILOS Seminar 2023-10-11:
Title: Towards Foundation Models for Graph Reasoning and AI 4 Science
Speaker: Michael Galkin, Research Scientist at Intel AI Lab
Abstract: Foundation models in graph learning are hard to design due to the lack of common invariances that transfer across different structures and domains. In this talk, I will give an overview of the two main tracks of my research at Intel AI: creating foundation models for knowledge graph reasoning that can run zero-shot inference on any multi-relational graphs, and foundation models for materials discovery in the AI4Science domain that capture physical properties of crystal structures and transfer to a variety of predictive and generative tasks. We will also talk about theoretical and practical challenges like scaling behavior, data scarcity, and diverse evaluation of foundation graph models.
Bio: Michael Galkin is a Research Scientist at Intel AI Lab in San Diego working on Graph Machine Learning and Geometric Deep Learning. Previously, he was a postdoc a
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