17 citations · 51 across the 11 of their papers we have counts for
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cs.LG2023
Distributed Matrix-Based Sampling for Graph Neural Network Training
Alok Tripathy, Katherine Yelick, Aydin Buluc
Graph Neural Networks (GNNs) offer a compact and computationally efficient way to learn embeddings and classifications on graph data. GNN models are frequently large, making distri…
cs.DC2023
Extreme-scale many-against-many protein similarity search
Oguz Selvitopi, Saliya Ekanayake, Giulia Guidi +7
Similarity search is one of the most fundamental computations that are regularly performed on ever-increasing protein datasets. Scalability is of paramount importance for uncoverin…