Don't miss out on our Webinar on PyG 2.5 - Distributed Training of GNNs tomorrow!
🗓️Wednesday, Mar 6th🕔5pm CET/ 8am PST
Register for free 👇
eventbrite.com/e/webinar-pyg-…
📢 We are hosting a webinar on March 6th 8am PT/5pm CET on the latest PyG release. The webinar covers everything you need to know about PyG 2.5, including a live demo on how set up and use our new distributed GNN training solution.
Register for free 👇
eventbrite.com/e/webinar-pyg-…
We just released PyG 2.4 🎉, including PyTorch 2.1 support, model compilation, on-disk datasets, neighbor sampling improvements, and much more. Thanks to 62 contributors who have made this release possible. Full release notes 👇
github.com/pyg-team/pytor…
A thread 🧵 [1/5]
PyG Town Hall one week from today! Join us as we discuss how to run graphML locally in just a few lines of code w the ArangoDB team
info.kumo.ai/pyg-town-hall-…
For anyone interested in learning more about graph learning for specific use cases, make sure to follow @Kumo_ai_team ! We'll be sharing many new application-specific experiences with GNNs there in the coming weeks!
Great blog post from the Kùzu team (Chang Liu and @semihsalihoglu) showing how they use the PyG Remote Backend to scale GNN models with one line of code!
kuzudb.com/blog/kuzu-pyg-…
Link prediction webinar is tomorrow - 5/16 at 10 PST! Tune in to learn more about how to build and scale link prediction with GNNs!
Register here: info.kumo.ai/link-predictio…
NVIDIA RAPIDS has just released their blog on training GNNs with cuGraph-PyG, an extension to PyG that enables large-scale training on trillion-edge graphs. This is the first in a series that will cover scaling PyG GNNs to massive-scale graphs
medium.com/rapids-ai/intr…
Register for our next webinar on link prediction! Learn more about how to build and scale link prediction for production use cases.
info.kumo.ai/link-predictio…
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