Abstract: Graph-based methods have demonstrated exceptional performance in semi-supervised classification. However, existing graph-based methods typically construct either a predefined graph in the ...
Already using NumPy, Pandas, and Scikit-learn? Here are seven more powerful data wrangling tools that deserve a place in your ...
U.S. EPA, Office of Research and Development, Athens, Georgia 30605, United States ...
Analysis and insights for driving a rapid transition to net-zero while building resilience to physical climate impacts ...
Communities often celebrate data center openings. But for all the benefits state and local officials tout for the massive facilities, they also bring their share of problems — including gobbling up ...
The industry believes AI will work its way into every corner of our lives, and so needs to build sufficient capacity to address that anticipated demand. But the hardware used to make AI work is so ...
Loads the trained Faster R-CNN model. Reads the input video frame by frame. For frames with weapons detected above a confidence threshold, saves the frame to a folder. Names the frames with the ...
Abstract: Equivariant quantum graph neural networks (EQGNNs) offer a potentially powerful method to process graph data. However, existing EQGNN models only consider the permutation symmetry of graphs, ...
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