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cs.LG2022
Scalable Graph Convolutional Network Training on Distributed-Memory Systems
Gunduz Vehbi Demirci, Aparajita Haldar, Hakan Ferhatosmanoglu
Graph Convolutional Networks (GCNs) are extensively utilized for deep learning on graphs. The large data sizes of graphs and their vertex features make scalable training algorithms…
cs.SI2022
Temporal Cascade Model for Analyzing Spread in Evolving Networks with Disease Monitoring Applications
Aparajita Haldar, Shuang Wang, Gunduz Demirci +2
Current approaches for modeling propagation in networks (e.g., spread of disease) are unable to adequately capture temporal properties of the data such as order and duration of evo…