By popular demand we are releasing lecture videos for Stanford CS224W Machine Learning with Graphs which focuses on graph representation learning. Two new lectures every week. Videos: youtube.com/playlist?list=…
Syllabus: cs224w.stanford.edu
🚀🎉 Excited to announce 🌟 PyTorch Frame 🌟 - our new open-source initiative in PyTorch! Dive into multi-modal tabular deep learning like never before!
Link: github.com/pyg-team/pytor…#PyTorch#OpenSource (1/6)
🎉 Excited and honored to receive the #SIGKDD Innovation Award for my contributions to #GraphMining, #NetworkScience, and applied #MachineLearning! Looking forward to advancing these fields even further! 🚀 I am grateful for all the amazing students and collaborators. Thank you
Stanford is proud to bring together leaders from academia&industry to showcase advances in Graph Neural Networks. Program includes applications, frameworks and industry panels on challenges of graph-based machine learning models. Register at: stanford.io/3BUbjjL
Ever wondered how much stay-at-home slows down COVID-19? In our latest @Nature paper we use smartphone data to model mobility of 98 million people and detect hotspots, track COVID-19, and guide reopening strategies. Try the model at covid-mobility.stanford.edu
Slides from my Stanford Graph Learning workshop showcasing recent advancements in Graph ML and new developments in PyG: i.stanford.edu/~jure/pub/talk…@PyG_Team
Excited to announce 2nd Stanford Graph Learning Workshop on Wed Sept 28th with leaders from academia and industry to showcase recent advances of Graph Representation Learning across a wide range of applications. Program & free registration: snap.stanford.edu/graphlearning-…
Excited to share our latest research: The myth of cosmopolitan cities: Why large urban areas are more segregated
Long-standing assumption is that large cities with their diverse population, foster diverse person-to-person interactions.
Our @Nature paper shows the opposite is
🌟 Excited to announce the Stanford Graph Learning Workshop 2023 on Oct 24 2023!🤝 Bringing together academia & industry leaders to delve into advances in #MachineLearning & #AI in Relational domains, Foundation models, and Multimodal AI. 📢 Free registration. 📢 Calling for
Stanford CS224W Machine Learning with Graphs. Lectures 7 & 8 posted! Design space for Graph Neural Networks, Graph Augmentation, and training of GNNs.
Videos: youtube.com/playlist?list=…
Syllabus: cs224w.stanford.edu