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
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
Codebase for simulating and estimating the Attractor-Based Coevolving Dot Product Random Graph Model (ABCDPRGM), a dynamic network model for analyzing polarization and flocking in graph data. Includes synthetic experiments and real-data analysis using Age of Empires IV ranked match data.
DANTE is a software tool for pairwise alignment of dynamic networks. It computes the topological node similarities via temporal embedding.
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