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

d3 plugin to create a temporal network visualization

🌟 Vertex Centric approach for building GNN/TGNNs

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

A Temporal Networks Library written in Python

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

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

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

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: