PyG

Graph Neural Network Library for PyTorch

[PyG @PyG_Team]

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 👇
https://t.co/n35PFm1FIZ

[Matthias Fey @rusty1s]

📢 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 👇
https://t.co/lLhGNJA72L

[Matthias Fey @rusty1s]

📢 Excited to release PyG (PyTorch Geometric) v2.5, including distributed training, a dedicated graph tensor representation, RecSys support, PyTorch 2.2 and native compilation support 🎉

Release Notes 👇
https://t.co/UWofWUZhku

🧵 A thread [1/6]

[Matthias Fey @rusty1s]

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 👇
https://t.co/S483b5xC9U

A thread 🧵 [1/5]

[PyG @PyG_Team]

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
https://t.co/4cKhUf5dM6

[PyG @PyG_Team]

Our next Webinar is on July 18th! Come learn about how GNNs can power growth and retention. Register here: https://t.co/QSxxVXByzT

[Kumo @Kumo_ai_team]

#AI powered personalization is becoming a realization engine for what users truly want in a world of unlimited choices.
https://t.co/3zgdgHjR6R

[Kumo @Kumo_ai_team]

Great post from the arango team on fastgraphml sharing their low code framework for performing ML on graphs:
https://t.co/PEDqmGbA5o

fastgraphml GitHub link: https://t.co/LZmTI2lPKb

[Kumo @Kumo_ai_team]

A great shortcut for building a recommender system with the latest in #GraphLearning
https://t.co/BEISNGmqCT

[Kumo @Kumo_ai_team]

Recording of our latest webinar on link prediction for recommendation and ranking is now live!
Watch it here: https://t.co/xYe05VW1qf

#gnn #pyg #personalization #recommendation

[PyG @PyG_Team]

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!

[PyG @PyG_Team]

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!
https://t.co/ud3h0oKER1

[PyG @PyG_Team]

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: https://t.co/ftB2CAFRAA

[PyG @PyG_Team]

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
https://t.co/ShT092RdRG

[PyG @PyG_Team]

Our next town hall is 5/25 - we'll hear from the Weights & Biases team on their work in point cloud segmentations:

https://t.co/vidVhoiDP6

[PyG @PyG_Team]

We have a new initiative allowing more folks to be core contributors! Interested in learning more? Check out our page!
https://t.co/FhMuWECO0w

[PyG @PyG_Team]

PyG Town Hall is tomorrow 10am PDT! Tune in to learn about how to leverage IPUs for training GNNs.
You can register here: https://t.co/s1JZ1xWkIh

[Jure Leskovec @jure]

Register for our next webinar on link prediction! Learn more about how to build and scale link prediction for production use cases.
https://t.co/grgf99wVCi

[PyG @PyG_Team]

our recording for the webinar is now live! You can watch here: https://t.co/v8oFb6LvEY

[PyG @PyG_Team]

Join us in 30 mins for our explainability webinar!
Register here: https://t.co/dpxF7IH1Vq