AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.

With AI’s power demands intensifying, SSDs are primed to overtake HDDs as the default choice for maximizing performance, ...

Abstract: Recent progress in research on deep graph networks (DGNs) has led to a maturation of the domain of learning on graphs. Despite the growth of this research field, there are still important ...

Kirchhoff graphs are a new type of graph, one whose edges are vectors. They depict the dependencies in sets of vectors, and in this regard, they are akin to matroids. Indeed every binary matroid is ...

This is a PyTorch implementation of the GraphCTA algorithm, which tries to address the domain adaptation problem without accessing the labelled source graph. It performs model adaptation and graph ...

Abstract: The increasing severity of traffic congestion has driven the application of deep reinforcement learning (DRL) in traffic signal control. It utilizes spatial states to interact with ...