A new technical paper titled “Massively parallel and universal approximation of nonlinear functions using diffractive processors” was published by researchers at UCLA. “Nonlinear computation is ...
Researchers at the University of California, Los Angeles (UCLA) have developed an optical computing framework that performs large-scale nonlinear computations using linear materials. Reported in ...
Victor Lee is director of product management at TigerGraph. Graph databases excel at answering complex questions about relationships in large data sets. But they hit a wall—in terms of both ...
Traditional neural networks don't take into account the relational inductive bias inherent in graph-structured data. GCNs solve this by aggregating features from a node's neighbors during learning, ...
Aggregation Step,Asynchronous System,Average Latency,Benchmark,Cache Hit,Complex Graph,Complex Queries,Distributed Database,Distribution Graph,Distribution System ...
Aggregation Step,Asynchronous System,Average Latency,Benchmark,Cache Hit,Communication Rounds,Complex Graph,Complex Queries,Concurrency Control,Direct Access ...
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