DeepGraphLibrary

Official twitter for Deep Graph Library (DGL) #DGL

[DeepGraphLibrary @DGLGraph]

Coming to #KDD2024? Mark your day by attending our tutorial "Graph Machine Learning Meets Multi-table Relational Data" on the first afternoon of the conference! @kdd_news @AmazonScience

Tutorial details: https://t.co/ozqMWoGGeR

[Yichuan Wang @YichuanM]

🎉 DiskGNN @SIGMODConf : Trained 300M+ node graphs (TB-scale) with just 1 GPU & <100GB RAM! Zero-overhead GPU/CPU/SSD pooling made it possible 🚀

[DeepGraphLibrary @DGLGraph]

* Consideration of the end-to-end process from tables to final predictions is critical to success."

Paper link: https://t.co/nDuqjkBnCk

A collaborative effort by @AmazonScience DGL team, @sjtu1896 , @PKU1898 , @Tsinghua_Uni , @FudanUni , @CarnegieMellon and many (3/3)

[DeepGraphLibrary @DGLGraph]

Excited to release DBInfer, a comprehensive benchmarking toolbox for evaluating predictive modeling over relational DBs. The DBInfer-Bench package offers 14 benchmarks covering real-world scenarios like recsys, event forecasting, anomaly detection. Repo: https://t.co/qmv4TtvOpq

[DeepGraphLibrary @DGLGraph]

Key findings from DBInfer-based comparisons of graph neural networks versus strong tabular baselines with feature engineering:
* No single winner, a great open space for new models!
* GNNs show the strongest performance, but the graph construction strategy matters too. (2/3)

[DeepGraphLibrary @DGLGraph]

DGL 2.1 with GPU-accelerated GraphBolt delivers blazing-fast data loading & stays flexible for customization. Plus, it works with PyTorch Geometric (PyG)!

👉Check out the blog for the release summary: https://t.co/J4MvzuJDyV

🧠Major Contributor: @mfbalin

#DGL #GML

[DeepGraphLibrary @DGLGraph]

Say goodbye to data loading bottlenecks! DGL 2.0 introduces GraphBolt, a revolutionary data pipeline framework that supercharges your GNN training.

👉Check out the blog for the release summary: https://t.co/TKW91Hm2qr

[DeepGraphLibrary @DGLGraph]

Accelerating GNN Training on Intel CPU with DGL through fused sampling & hybrid partitioning, which can give you up to a 2x speedup! 🚀🧠 Awesome work done by Hesham (https://t.co/vaoup2Bt3a) and Adam (https://t.co/C8lVdeLF7M). @IntelAI @IntelBusiness

https://t.co/hmRVSh9gO0

[Amazon Science @AmazonScience]

Amazon has publicly released RefChecker, a combination tool and dataset that detects hallucinations in #LLMs. To characterize factual claims, RefChecker uses knowledge triplets rather than natural language, enabling finer-grained judgments. #GenerativeAI https://t.co/uP1bi3hmMk

[DeepGraphLibrary @DGLGraph]

Project GitHub: https://t.co/0mHzHUEixK

Demo: https://t.co/iHr2Vx0qfc

(2/2)

[DeepGraphLibrary @DGLGraph]

Knowledge graph still rocks in the LLM era! Here is BSChecker🕵️, a new tool leveraging knowledge triplets to flag fine-grain hallucination of LLMs responses in zero/noise/accurate contexts. Demo and Github links below 👇 (1/2)

[DeepGraphLibrary @DGLGraph]

@LogConference

[DeepGraphLibrary @DGLGraph]

DGL team will be joining @LogConference Shanghai local meet-up to share our recent development. Event link: https://t.co/TYhSUVs38M https://t.co/goXycy0bAP . Find out more LoG local meet-ups nearby in the reply 👇

[Xavier Bresson @xbresson]

Will give a talk tomorrow Sunday 10am at the workshop Graph Learning Benchmarks @GLB_Workshop #KDD2023 w/ @YizhouSun, @jimeng, Z. Da @DGLGraph, A. Wang
https://t.co/zTqE7FoCnY

Thanks to the organizers!

Also glad to meet and chat about research during the conference 😀

[Xavier Bresson @xbresson]

Da Zheng @DGLGraph "Graph machine learning for industry applications with DGL and GraphStorm" #KDD2023

[DeepGraphLibrary @DGLGraph]

A new offering from the team! Announcing GraphStorm, a low-code framework for enterprise-level graph machine learning. See how it empowers GML in business 👇https://t.co/gNxtWzgoY0

[Xavier Bresson @xbresson]

If new with graph learning, here is a warm-up notebook to learn to use graphs:
• Build graph w/ features and compute basic message-passing function w/ @DGLGraph
• Convert into graph formats w/ DGL, NetworkX, dense/sparse PyTorch
• Visualize graph

Code: https://t.co/vbb5YFqZiU

[Xavier Bresson @xbresson]

Ever wanted to code Graph Transformer (GT) from *scratch* using a few lines of code with @PyTorch and @DGLGraph? :)

See below my course material

Slides: https://t.co/XzyLT79oam
GitHub: https://t.co/hhSogRe31V
Paper: https://t.co/nPHiFTtty6

Coding GT step-by-step 👇

[DeepGraphLibrary @DGLGraph]

For more information, check out the tutorial page https://t.co/HEvE2JKHrA or join our slack https://t.co/zktblT9a8E channel "webconf23-tutorial".

[DeepGraphLibrary @DGLGraph]

Interested in DGL v1.0? Wanna try out the new sparse APIs for Graph ML? The team will host an hands-on tutorial @TheWebConf'23 on May 1st 1:30pm. Join us! #WWW23 #TheWebConf

Video teaser: https://t.co/degI8h9y1M