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Greatest papers with code

Learning Temporal Attention in Dynamic Graphs with Bilinear Interactions

23 Sep 2019uoguelph-mlrg/LDG

We consider a common case in which edges can be short term interactions (e. g., messaging) or long term structural connections (e. g., friendship).

DYNAMIC LINK PREDICTION POINT PROCESSES

Variational Graph Recurrent Neural Networks

NeurIPS 2019 VGraphRNN/VGRNN

Representation learning over graph structured data has been mostly studied in static graph settings while efforts for modeling dynamic graphs are still scant.

DYNAMIC LINK PREDICTION REPRESENTATION LEARNING VARIATIONAL INFERENCE