Google Meet Link: https://meet.google.com/yko-cpuk-czg
Slides: https://drive.google.com/file/d/1ECcnRgJqjmj7hlegYuPdscLCUw7YJc7G/view?usp=sharing
Mon 7:30 a.m. - 7:40 a.m.
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Welcome
(
Introduction
)
|
Bryan Perozzi 🔗 |
Mon 7:40 a.m. - 8:00 a.m.
|
GNN Basics
(
Talk
)
A brief overview of GNNs and motivation for TF-GNN. |
Sami A Abu-El-Haija 🔗 |
Mon 8:00 a.m. - 8:20 a.m.
|
TF-GNN Basics (Hands on)
(
Demonstration
)
Overview of running TF-GNN models on small scale, in-memory datasets. |
Sami A Abu-El-Haija 🔗 |
Mon 8:20 a.m. - 8:30 a.m.
|
Break
|
🔗 |
Mon 8:30 a.m. - 8:50 a.m.
|
TF-GNN Modeling
(
Talk
)
A more detailed dive into data representation and modeling primitives available in TF-GNN. |
Neslihan Bulut 🔗 |
Mon 8:50 a.m. - 9:20 a.m.
|
TF-GNN Modeling (Hands on)
(
Demonstration
)
Hands-on walk through a notebook illustrating how to use and create a TF-GNN model. |
Neslihan Bulut 🔗 |
Mon 9:20 a.m. - 9:30 a.m.
|
Break
|
🔗 |
Mon 9:30 a.m. - 9:50 a.m.
|
Running TF-GNN at Scale
(
Talk
)
Covers how to run TF-GNN at scale, covering: 1) Common ML system architectures 2) Batch architectures for scaling Graph Neural Networks 3) Introduction to Apache Beam for Scalable Graph Sub-Sampling |
Brandon Mayer 🔗 |
Mon 9:50 a.m. - 10:20 a.m.
|
Running TF-GNN at Scale (Hands on)
(
Demonstration
)
Hands-on walk through a notebook illustrating using TF-GNN with cloud computing. Covers distributed sampling, and model training with VertexAI. |
Brandon Mayer 🔗 |
Mon 10:20 a.m. - 10:25 a.m.
|
Closing
|
Anton Tsitsulin 🔗 |