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Stanford Graph Learning Workshop 2024
Stanford Data Science Affiliates Program
Event Details:
Tuesday, November 5, 2024
9:00am - 6:00pm PST
Location
Paul Brest Hall
555 Salvatierra Walk
Stanford, CA 94305
United States
The workshop will bring together leaders from academia and industry to showcase recent advances in Machine Learning and AI in Relational domains, Foundation Models, and Agents. The workshop will discuss methodological advancements, a wide range of applications to different domains, machine learning frameworks and practical challenges for large-scale training and deployment of AI models.
Agenda
The event will take place at Stanford University and will be live-streamed online.
08:00 - 09:00 | Registration & Breakfast | |
09:00 - 09:10 | Jure Leskovec, Stanford University | Welcome and Overview |
09:10 - 09:30 | Matthias Fey & Akhiro Nitta, PyG & Kumo.AI | What’s New in PyG |
09:30 - 09:50 | Joshua Robinson, Isomorphic Labs & Stanford | Relational Deep Learning - Graph Representation Learning on Relational Databases |
09:50 - 10:10 | Rishabh Ranjan, Stanford University | RelBench: A Benchmark for Deep Learning on Relational Databases |
10:10 - 10:30 | Rishi Puri, NVIDIA | GNN+LLM in PyG |
10:30 - 11:00 | Break | |
11:00 - 11:20 | Kexin Huang, Stanford University | Small-cohort GWAS discovery with AI over massive functional genomics knowledge graph |
11:20 - 11:40 | Yanay Rosen, Stanford University | Universal Cell Embeddings and towards the AI Virtual Cell |
11:40 - 12:00 | Marcel Roed, Stanford University | Lessons from Training Large Foundation Models |
12:00 - 13:30 | Lunch | |
13:30 - 13:50 | Vassilis N. Ioannidis, Amazon | Enhancing LLMs with structured data |
13:50 - 14:10 | Charilaos Kanatsoulis, Stanford University | Towards Next Generation Graph Transformers |
14:10 - 14:30 | Blaz Stojanovic, Kumo.AI | ContextGNN: Beyond Two-Tower Recommendation Systems |
14:30 - 15:00 | Break | |
15:00-15:20 | Yusuf Roohani, Arc Institute & Stanford | An AI Agent for Designing Biological Experiments |
15:20-15:40 | Minkai Xu, Stanford University | Diffusion Models for Tabular Data Generation |
15:40-16:00 | Swapnil Bembde, Hitachi America Ltd. | Learning Production Functions for Supply Chains with Graph Neural Networks |
16:00-16:15 | Poster slam | |
16:15 - 18:00 | Happy Hour & Poster Session |
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