IEEE

S2G-GCN: A Plot Classification Network Integrating Spectrum-to-Graph Modeling and Graph Convolutional Network for Compact HFSWR

Abstract: Plot classification refers to the identification of true target plots among initial detections, and it is crucial for target tracking with compact high-frequency surface wave radar (HFSWR) ...
Dot Physics on MSN

Mastering animated graphs in GlowScript: VPython made easy

Learn how to create dynamic, animated graphs in GlowScript using VPython with ease! 📊 This step-by-step tutorial guides you through visualizing data, animating simulations, and mastering interactive ...
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

Graph-theoretical optimization of fusion-based graph state generation.

OptGraphState is a python package that implements the graph-theoretical strategy to optimize the fusion-based generation of any graph state, which is proposed in Lee & Jeong, Quantum 7, 1212 (2023).