[TPAMI 2024] Awesome Resources of GNNs for Time Series Analysis (GNN4TS)
Archive of Temporal Knowledge Reasoning in Social Network and Knowledge Graph
Representation learning on dynamic graphs using self-attention networks
A collection of resources on dynamic/streaming/temporal/evolving graph processing systems, databases, data structures, datasets, and related academic and industrial work
Variational Graph Recurrent Neural Networks - PyTorch
CTGCN: k-core based Temporal Graph Convolutional Network for Dynamic Graphs (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9240056
Linked Dynamic Graph CNN: Learning through Point Cloud by Linking Hierarchical Features
[AAAI 2023] Scaling Up Dynamic Graph Representation Learning via Spiking Neural Networks
A paper list of research about social knowledge graph
[ACM Computing Surveys'23] Implementations or refactor of some temporal link prediction/dynamic link prediction methods and summary of related open resources for survey paper "Temporal Link Prediction: A Unified Framework, Taxonomy, and Review" which has been accepted by ACM Computing Surveys.
[NeurIPS 2022] The official PyTorch implementation of "Neural Temporal Walks: Motif-Aware Representation Learning on Continuous-Time Dynamic Graphs"
[ICDM 2020] Python implementation for "Dynamic Graph Collaborative Filtering."
Code for "Graph Neural Networks for Friend Ranking in Large-scale Social Platforms" (WWW 2021).
Implementation codes for KDD24 paper "LLM4DyG: Can Large Language Models Solve Spatial-Temporal Problems on Dynamic Graphs?"
Source code of "RapidFlow: An Efficient Approach to Continuous Subgraph Matching" published in VLDB'2022 - By Shixuan Sun, Xibo Sun, Bingsheng He and Qiong Luo
Anomaly Detection in Dynamic Graphs
[CVPR'25 Highlight] The official implementation of "GG-SSMs: Graph-Generating State Space Models"
The official repository for the paper "Deep learning for dynamic graphs: models and benchmarks" accepted at IEEE TNNLS
Official reference implementation of our paper "Temporal Graph ODEs for Irregularly-Sampled Time Series" accepted at IJCAI 24
DYnamic MOtif-NoDes (DYMOND) is a dynamic network generative model based on temporal motifs and node behavior.
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