3 papers
cs.SI2019
Multi-MotifGAN (MMGAN): Motif-targeted Graph Generation and Prediction
Anuththari Gamage, Eli Chien, Jianhao Peng +1
Generative graph models create instances of graphs that mimic the properties of real-world networks. Generative models are successful at retaining pairwise associations in the unde…
stat.ML2018
Multi-View Graph Embedding Using Randomized Shortest Paths
Anuththari Gamage, Brian Rappaport, Shuchin Aeron +1
Real-world data sets often provide multiple types of information about the same set of entities. This data is well represented by multi-view graphs, which consist of several distin…
stat.ML2017
Faster Clustering via Non-Backtracking Random Walks
Brian Rappaport, Anuththari Gamage, Shuchin Aeron
This paper presents VEC-NBT, a variation on the unsupervised graph clustering technique VEC, which improves upon the performance of the original algorithm significantly for sparse…