The recent past has seen an increasing interest in Heterogeneous Graph Neural Networks (HGNNs), since many real-world graphs are heterogeneous in nature, from citation graphs to email graphs. However, ...
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Abstract: The existence of missing values in time-series data has brought great inconvenience to our lives. In this paper, we propose a Stacked Spatio-Temporal Graph ...
The Supporting Information is available free of charge at https://pubs.acs.org/doi/10.1021/acs.jcim.5c01525. Efficiency analysis of different normalization strategies ...
In telecommunication applications, target impedance serves as a crucial benchmark for power distribution network (PDN) design. It ensures that the die operates within an acceptable level of rail ...
Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...
Abstract: As the demand for electricity keeps rising, distribution networks are expanding in scale and becoming more complex. Accurately and efficiently assessing the state of these networks is ...
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 ...
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