7 citations · 16 across the 22 of their papers we have counts for
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cs.DC2023
FastSample: Accelerating Distributed Graph Neural Network Training for Billion-Scale Graphs
Hesham Mostafa, Adam Grabowski, Md Asadullah Turja +3
Training Graph Neural Networks(GNNs) on a large monolithic graph presents unique challenges as the graph cannot fit within a single machine and it cannot be decomposed into smaller…
cs.LG2023★ 1 cited
Intrinsically motivated graph exploration using network theories of human curiosity
Shubhankar P. Patankar, Mathieu Ouellet, Juan Cervino +3
Intrinsically motivated exploration has proven useful for reinforcement learning, even without additional extrinsic rewards. When the environment is naturally represented as a grap…