GitHub

STM-Graph: A Python Framework for Spatio-Temporal Mapping and Graph Neural Network Predictions

STM-Graph is a Python framework for analyzing spatial-temporal urban data and doing predictions using Graph Neural Networks. It provides a complete end-to-end pipeline from raw event data to trained ...
How-To Geek on MSN

I install these 9 Python tools on every new machine

These are my go-to libraries for Python data crunching.
IEEE

Rotation- and Permutation-Equivariant Quantum Graph Neural Network for 3D Graph Data

Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
GitHub

(ICLR 2024 Oral) Mixed-Type Tabular Data Synthesis with Score-based Diffusion in Latent Space

[2024-06-20]: Disable loading irrelvent packages when training individual models; update the instruction for DCR experiements; fix minor bugs in TabSyn's training script. [2024-05-14]: Add demo code ...
IEEE

A Preliminary Study on Dynamic Urban Knowledge Graph Construction using Heterogeneous ...

Abstract: Knowledge Graphs (KGs) have recently emerged as a powerful tool for extracting directed multi-relational "knowledge" from structured facts within massive urban mobility data, supporting ...