Making tabular machine learning easy with PyToch Frame. Check it out!

#LasVegas

📢 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 👇 github.com/pyg-team/pytor… 🧵 A thread [1/6]

🚀 Join us for a special webinar on March 6th, 8am PT/5pm CET, as we unveil the latest in GNN technology - PyG 2.5! 🎉 Dive deep into the features with a live demo on setting up and using our new distributed GNN training solution. A stellar collaboration between Kumo

Check out our PyTorch Frame tech report arxiv.org/abs/2404.00776 We aim to push tabular deep learning to handle complex multi-modal, multi-tabular data, beyond conventional single-tabular data. We do so by seamlessly integrating PyTorch Frame with LLMs and Graph Neural Nets!

Excited about the release of the Hybrid GNN blog post, from my time at Kumo! docs.kumo.ai/docs/hybrid-gr… A single, sophisticated GNN model to achieve SoTA on recommendation. Deployed to many customers to generate huge (e.g., $100 million) additional sales. Check it out!

🚀 Announcing RelBench: an open benchmark for deep learning on relational databases! RelBench is the foundational infrastructure for research in Relational Deep Learning (RDL), which brings modern AI to structured data. RelBench has databases, tasks, loaders, evaluators, and

Students at Stanford have built alphaXiv, an open discussion forum for arXiv papers.

🚀 GraphRAG: Boost Retrieval Accuracy and RAG Performance! Check out the diagram and tech stack below to see how this works. 🔹CAMEL-AI.org: A multi-agent system framework that facilitates the workflow and provides agents such as Knowledge Graph Agent and Chat Agent.

PyG 2.6 is here, including new models and examples on how to combine GNNs with LLMs! Thanks to many contributors who have made this release possible. Full release notes👇 github.com/pyg-team/pytor…

#southpointpark #Hawaii #bigisland

#Hawaii #Hilo #coconutisland

🎉 Excited to announce the release of ContextGNN, our state-of-art and scalable recommendation model from Kumo! 🔗 ContextGNN paper: arxiv.org/abs/2411.19513 What makes ContextGNN unique? It combines pair-wise and two-tower representations into a single architecture, enabling

Thrilled to present PyTorch Frame at NeurIPS Conference this Saturday! 🚀 PyTorch Frame is a cutting-edge tabular deep learning framework supporting: ✅ multi-modal data ✅ various existing models via modular design ✅ integration with GNNs & foundation models

Looking forward to connecting with everyone at Table Representation Learning @NeurIPS and sharing insights on this exciting project! 🙌 A big shout-out to my amazing co-authors Weihua Hu, Yiwen Yuan, Zecheng Zhang, Kaidi Cao, Vid Kocijan, Jure Leskovec and Matthias Fey 🙌

🎉 PyTorch Frame, our open-source tabular deep learning framework, won the Best Paper Award 🏆 at Table Representation Learning @NeurIPS at NeurIPS Conference 2024! Huge congrats to Kumo PyG: Weihua Hu Yiwen Yuan Zecheng Zhang, Kaidi Cao, Vid Kocijan, Jinu Sunil, Jure Leskovec, and Matthias Fey! 🙌

I am still too young too simple, sometimes naive😂

🚀 Day 0: Warming up for #OpenSourceWeek! We're a tiny team DeepSeek exploring AGI. Starting next week, we'll be open-sourcing 5 repos, sharing our small but sincere progress with full transparency. These humble building blocks in our online service have been documented,

You can build the best Web agent with today's Github trending repos. Don't ask me how 🫡 Mem0 x CAMEL: github.com/camel-ai/camel… BrowserUse x CAMEL: github.com/camel-ai/camel…

🚀 Introducing KumoRFM — the world’s first Relational Foundation Model purpose-built for enterprise prediction tasks! KumoRFM reasons over complex relational data to deliver instant, accurate, in-context predictions — no task-specific model training required. A true game-changer