Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I really like to use numerical calculations without all the fancy programming ...

python -u -m graph_qa.train.trainer \ --graph artifacts/vn2_graph_full_temporal_v2.jsonl \ --epochs 10 --batch-size 512 --K 30 --hops 1 \ --hidden-dim 64 --num-layers ...

I co-created Graph Neural Networks while at Stanford. I recognized early on that this technology was incredibly powerful. Every data point, every observation, every piece of knowledge doesn’t exist in ...

This project demonstrates how to convert a traditional relational database table into a knowledge graph using Neo4j, enabling powerful relationship-based analysis that would be difficult or impossible ...

Introduction: The decision regarding the supply of emergency equipments for power emergencies requires timeliness, efficiency, and accuracy. The multi-agent supply ...

Today, it takes months to build predictive models using machine learning — KumoRFM delivers results in seconds, with no manual effort. AI has completely transformed how businesses leverage text-based ...

Abstract: Graph Neural Networks (GNNs) have recently achieved remarkable success in various learning tasks involving graph-structured data. However, their application to multi-relational graph anomaly ...