graph neural networks

Every Locale Has Its Rhythm: Endow Time-Series Transformers with Spatial Insights for Long-term Spatio-Temporal Forecasting

Transformers have demonstrated promise in time-series forecasting, attributed to their superior capability of capturing temporal dependencies. Nevertheless, prevailing transformer models predominantly concentrate on the temporal dependencies within single-/multi-variate time series. This focus results in insufficient c...

Physics-Informed Graph Neural Networks for N-Body Dark Matter Halo Dynamics and Symplectic Orbital Integration Technical Monograph & Computational Astrophysics Architecture

GraphLLM4CTR: Large Language Model-Enhanced Graph Neural Networks for Click-through Rate Prediction in Recommender Systems

Click-through rate (CTR) prediction is a crucial task to estimate the probability that users will click on items in online platforms. Recently, researchers have incorporated semantics derived from large language models (LLMs) into representations of users and items in graph neural networks (GNNs) framework to facilitat...

Credit Scoring Dataset

This repository contains the dataset used in the paper titled "SPSEG: Soft Priors Guided and Community Structure Enhanced Graph Neural Networks for Enterprise Credit Assessment".

Consistent Vulnerability Detection Using Graph Neural Networks

FFmpg+Qemu: https://drive.google.com/drive/folders/1fz5Eunyy8k2YCXvoCIYPyVdruQ7Ch1cU?usp=sharing BigVul: https://drive.google.com/drive/folders/1hswJoJLhdFfUNA2eP1CH8ea7ybuNRy-o?usp=sharing ReposVul: https://drive.google.com/drive/folders/19NJ2twQ1GHLSw0cAPYI5Gn-kljFZ-MHF?usp=sharing

Credit Scoring Dataset

This repository contains the dataset used in the paper titled "SPSEG: Soft Priors Guided and Community Structure Enhanced Graph Neural Networks for Enterprise Credit Assessment".

Physics-Informed Graph Neural Networks for Dynamical Systems with Symplectic Velocity-Verlet Integration

A Comparative Review of Machine Learning Algorithms for Weather Prediction: Performance, Challenges, and Future Perspectives

Weather prediction is a complex forecasting problem because atmospheric variables interact across time and space, observations are heterogeneous, and useful forecasts must remain reliable across different lead times and weather regimes. Numerical weather prediction (NWP) remains a major operational approach, while mach...

CAST-GNN Dataset and materials for Continual Adaptive Learning for Custom Spatio-Temporal Knowledge Graphs via GNNs

CAST-GNN first release Data and code for the paper CAST-GNN: Continual Adaptive Learning for Custom Spatio-Temporal Knowledge Graphs via Graph Neural Networks [1]. [1] G. A. T. Özbulak, Y. R. Shrestha and J. -P. Calbimonte, "CAST-GNN: Continual Adaptive Learning for Custom Spatio-Temporal Knowledge Graphs via Graph Neu...

Consistent Vulnerability Detection Using Graph Neural Networks

Consistent Vulnerability Detection Using Graph Neural Networks

FFmpg+Qemu: https://drive.google.com/drive/folders/1fz5Eunyy8k2YCXvoCIYPyVdruQ7Ch1cU?usp=sharing BigVul: https://drive.google.com/drive/folders/1hswJoJLhdFfUNA2eP1CH8ea7ybuNRy-o?usp=sharing ReposVul: https://drive.google.com/drive/folders/19NJ2twQ1GHLSw0cAPYI5Gn-kljFZ-MHF?usp=sharing

CAST-GNN Dataset and materials for Continual Adaptive Learning for Custom Spatio-Temporal Knowledge Graphs via GNNs

CAST-GNN first release Data and code for the paper CAST-GNN: Continual Adaptive Learning for Custom Spatio-Temporal Knowledge Graphs via Graph Neural Networks [1]. [1] G. A. T. Özbulak, Y. R. Shrestha and J. -P. Calbimonte, "CAST-GNN: Continual Adaptive Learning for Custom Spatio-Temporal Knowledge Graphs via Graph Neu...