Suijian Zhou

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A number of graph-structured computing abstractions have been proposed to address the needs of solving complex and large-scale graph algorithms. Distributed Graphlab and its successor, PowerGraph, are two such frameworks that have demonstrated excellent performance with high scalability and fault tolerance. However, excessive communication and state sharing(More)
Rapid, robust computation of effective connectivity between neural regions is an important next step in characterizing the brain's organization, particularly in the resting state. However, recent work has called into question the value of causal inference computed directly from BOLD, demonstrating that valid inferences require transformation of the BOLD(More)
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