This repository contains a refactoring of the code used in the paper "Learning Latent Graph Structures and Their Uncertainty" (ICML 2025). The code is designed to be modular and easy to use, allowing ...

Want to master data fitting in Python? 📊🐍 In this video, we’ll walk you through using the least squares method to fit data and graph it using Python. Perfect for data science and stats enthusiasts!

Graphs are everywhere. From technology to finance, they often model valuable information such as people, networks, biological pathways and more. Often, scientists and technologists need to come up ...

Abstract: Graph neural networks (GNNs), as a cutting-edge technology in deep learning, perform particularly well in various tasks that process graph structure data. However, their foundation on ...

AI has changed the way searching happens—and that, in turn, has changed how discovery works. With tools like Perplexity, ChatGPT, and Gemini, the way they crawl the web is completely different from ...

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 ...

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 ...

Field and Space Experimental Robotics (FASER) Laboratory, Mechanical Engineering Department, Virginia Polytechnic Institute and State University, Blacksburg, VA, United States This article proposes a ...

GUI design can be a tedious job, requiring the use of specialist design tools and finding a suitable library that fits your use case. If you’re looking for a lightweight solution, though, you might ...

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 ...