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FuseIM: Fusing Probabilistic Traversals for Influence Maximization on Exascale Systems

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Picasso: Memory-Efficient Graph Coloring Using Palettes With Applications in Quantum Computing

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DS-GL: Advancing Graph Learning via Harnessing the Power of Nature within Dynamic Systems

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Red-QAOA: Efficient Variational Optimization through Circuit Reduction

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Fast Parallel Tensor Times Same Vector for Hypergraphs

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Faster approximate subgraph counts with privacy

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GLIMPSE of Future Power Grid Models

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AGS-GNN: Attribute-guided Sampling for Graph Neural Networks

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Visualizing Comparisons of Bill of Materials

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Distributed Multi-GPU Community Detection on Exascale Computing Platforms