ABSTRACT: Foot-and-Mouth Disease (FMD) remains a critical threat to global livestock industries, causing severe economic losses and trade restrictions. This paper proposes a novel application of ...
ABSTRACT: The accurate prediction of backbreak, a crucial parameter in mining operations, has a significant influence on safety and operational efficiency. The occurrence of this phenomenon is ...
Abstract: Graph convolutional networks (GCNs) have attracted significant attention in the field of multi-view learning, as they effectively extract intricate information from diverse features.
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Protein function prediction is essential for elucidating biological processes and ...
Abstract: By focusing on the structure exploration and information propagation from non-Euclidean data space, graph convolutional neural network (GCN), which can extract abundant and discriminative ...
Google published details of a new kind of AI based on graphs called a Graph Foundation Model (GFM) that generalizes to previously unseen graphs and delivers a three to forty times boost in precision ...
BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
Abstract: Many modern classification problems involve data that live in high-dimensional spaces but exhibit strong low-dimensional structure. Motivated by the manifold hypothesis, this talk presents a ...
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