GitHub

Graph Neural Networks for Tabular Data Learning (GNN4TDL)

The deep learning-based approaches to Tabular Data Learning (TDL), classification and regression, have shown competing performance, compared to their conventional counterparts. However, the latent ...
IEEE

Distributed Graph Learning From Smooth Data: A Bayesian Framework

Abstract: The emerging field of graph learning, which aims to learn reasonable graph structures from data, plays a vital role in Graph Signal Processing (GSP) and finds applications in various data ...
GitHub

dabeaz-course/python-mastery: Advanced Python Mastery (course by @dabeaz)

An exercise-driven course on Advanced Python Programming that was battle-tested several hundred times on the corporate-training circuit for more than a decade. Written by David Beazley, author of the ...
IEEE

Line-Level Defect Prediction by Capturing Code Contexts With Graph Convolutional Networks

Abstract: Software defect prediction refers to the systematic analysis and review of software using various approaches and tools to identify potential defects or errors. Software defect prediction ...
E&E

Data center ‘extension cord’ draws landowners’ ire

A developer for OpenAI and Oracle is facing stiff opposition to a proposed $1.4 billion transmission line for its Stargate project in Wisconsin. SAUKVILLE, Wisconsin — David Aversa spent months ...