GitHub

Graph Positional Autoencoders as Self-supervised Learners (GraphPAE)

accelerate==0.33.0 numpy==1.24.4 ogb==1.3.6 pandas==2.2.3 PyYAML==6.0.2 rdkit_pypi==2022.9.5 scikit_learn==1.3.2 scipy==1.8.1 torch==2.1.2+cu121 torch_geometric==2.6.1 torch_scatter==2.1.2+pt21cu121 ...
GitHub

AnomalyGFM: Graph Foundation Model for Zero/Few-shot Anomaly Detection

1️⃣ AnomalyGFM is the first GAD-oriented GFM with strong zero-shot and few-shot generalization abilities. 2️⃣ AnomalyGFM is pre-trained to learn discriminative, graph-agnostic class prototypes with ...
IEEE

A Survey on Graph Neural Networks for Time Series: Forecasting, Classification, Imputation, and Anomaly Detection

Abstract: Time series are the primary data type used to record dynamic system measurements and generated in great volume by both physical sensors and online processes (virtual sensors). Time series ...
IEEE

Linking Text and Visualizations via Contextual Knowledge Graph

Abstract: The integration of visualizations and text is commonly found in data news, analytical reports, and interactive documents. For example, financial articles are presented along with interactive ...