PyTorch Geometric Temporal: Spatiotemporal Signal Processing with Neural Machine Learning Models (CIKM 2021)

[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)

A versioning data store for time-variant graph data.

tsl: a PyTorch library for processing spatiotemporal data.

A collection of resources on dynamic/streaming/temporal/evolving graph processing systems, databases, data structures, datasets, and related academic and industrial work

Awesome Temporal Graph Learning is a collection of SOTA, novel temporal graph learning methods (papers, codes, and datasets).

Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"

Temporal Graph Analysis with TGX

🌟 Vertex Centric approach for building GNN/TGNNs

d3 plugin to create a temporal network visualization

Official reference implementation of our paper "Temporal Graph ODEs for Irregularly-Sampled Time Series" accepted at IJCAI 24

Anomaly detection in time-series networks. Spatio-temporal Anomaly Detection

A Temporal Networks Library written in Python

omnikeeper is a general-purpose and highly flexible data store solution and application framework

A collection of resources on dynamic/streaming/temporal/evolving graph processing systems, databases, data structures, datasets, and related academic and industrial work

Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift

[TKDE'23] Demo code of the paper entitled "High-Quality Temporal Link Prediction for Weighted Dynamic Graphs via Inductive Embedding Aggregation", which has been accepted by IEEE TKDE

Data and code repository from "Time-varying graph representation learning via higher-order skip-gram with negative sampling"

Code for the Big Data 2019 Paper - Temporal Neighbourhood Aggregation: Predicting Future Links in Temporal Graphs via Recurrent Variational Graph Convolutions

A prototype implementation of stream_graphs: