Due to the technological conditions and application demands of that time, although artificial intelligence appeared during the Third Industrial Revolution, it did not have a significant impact on ...
Abstract: Graph theoretical analysis is a powerful tool for quantitatively evaluating brain connectivity networks. Conventionally, brain connectivity is assumed to be temporally stationary, whereas ...
The decline in religiosity over the past 15 years is twice as great as the decline in 1960s and 1970s. An update through 2013 is now available here. Religiosity in the United States is in the midst of ...
Abstract: Recent advances in Graph Convolutional Neural Networks (GCNNs) have shown their efficiency for nonEuclidean data on graphs, which often require a large amount of labeled data with high cost.
A professionally curated list of awesome resources (paper, code, data, etc.) on Deep Graph Anomaly Detection (DGAD), which is the first work to comprehensively and systematically summarize the recent ...
This code was tested with PyTorch 2.0.1, cuda 11.8 and torch_geometrics 2.3.1. Note that ${PROJECT_DIR} refers to this directory. The following section outlines the graph-to-graph transformation ...
Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...
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