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Found 4 papers, 1 papers with code
Time to Cite: Modeling Citation Networks using the Dynamic Impact Single-Event Embedding Model
Using this likelihood, we propose the Dynamic Impact Single-Event Embedding model (DISEE).
Continuous-time Graph Representation with Sequential Survival Process
We apply the developed framework to a recent continuous time dynamic latent distance model characterizing network dynamics in terms of a sequence of piecewise linear movements of nodes in latent space.
Scalable Hierarchical Embeddings of Complex Networks
Graph representation learning has become important in order to understand and predict intrinsic structures in complex networks.
Multiple Kernel Representation Learning on Networks
In particular, we propose a weighted matrix factorization model that encodes random walk-based information about nodes of the network.
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