Many applications in important problem domains such as machine learning ...
Graph transformer networks (GTN) are a variant of graph convolutional
ne...
Numerical solutions to the Eikonal equation are computed using variants ...
Hypergraph partitioning is used in many problem domains including VLSI
d...
Graph pattern mining (GPM) is used in diverse application areas includin...
Betweenness centrality (BC) is an important graph analytical application...
We show that it is possible to obtain reliable prognoses about cancer
dy...
Load balancing graph analytics workloads on GPUs is difficult because of...
There is growing interest in graph mining algorithms such as motif count...
Intel Optane DC Persistent Memory is a new kind of byte-addressable memo...
Simultaneous Localization and Mapping (SLAM) is the problem of construct...
Acceleration of graph applications on GPUs has found large interest due ...
Approximate computing trades off accuracy of results for resources such ...