Awesome papers about machine learning (deep learning) on dynamic (temporal) graphs (networks / knowledge graphs).
GloDyNE: Global Topology Preserving Dynamic Network Embedding (accepted by IEEE TKDE in 2020) https://ieeexplore.ieee.org/document/9302718
Advances on machine learning of dynamic (temporal) graphs, covering the reading list of recent top academic conferences.
Code and dataset for IEEE TKDE paper "Dynamic Heterogeneous Information Network Embedding with Meta-path based Proximity"
Source code for CIKM 2019 paper "Temporal Network Embedding with Micro- and Macro-dynamics"
SG-EDNE: Skip-Gram based Ensembles Dynamic Network Embedding (for our paper "Robust Dynamic Network Embedding via Ensembles")
[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
Compact time- and attribute-aware node representations
DANTE is a software tool for pairwise alignment of dynamic networks. It computes the topological node similarities via temporal embedding.
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