Recent augmentation-based methods showed that message-passing (MP) neural networks often perform poorly on low-degree nodes, leading to degree biases due to a lack of messages reaching low-degree ...
Abstract: This article presents a graph theory-informed approach to state estimation-based model selection for identifying the operational topology of a power distribution system. The proposed method ...
Abstract: Heterogeneous graph neural networks (HGNNs) have demonstrated promising capabilities in addressing various problems defined on heterogeneous graphs containing multiple types of nodes or ...
To some, METR’s “time horizon plot” indicates that AI utopia—or apocalypse—is close at hand. The truth is more complicated. MIT Technology Review Explains: Let our writers untangle the complex, messy ...
Raster-to-Graph is a novel automatic recognition framework, which achieves structural and semantic recognition of floorplans, addresses the problem of obtaining high-quality vectorized floorplans from ...
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