We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors ...
Abstract: The increasing deployment of solar photovoltaic (PV) systems in the electric grid, aimed at addressing the energy crisis and surging power demands, has expanded the potential vulnerability ...
Abstract: The large-scale integration of wind power into power systems presents serious challenges to their safety and stability, making accurate wind power output prediction a critical research focus ...
This is the PyTorch implementation for DiffKG proposed in the paper DiffKG: Knowledge Graph Diffusion Model for Recommendation, which is accepted by WSDM 2024 Oral. Yangqin Jiang, Yuhao Yang, Lianghao ...
3D image display is essential for next-generation volumetric imaging; however, dense depth multiplexing for 3D image projection remains challenging because diffraction-induced cross-talk rapidly ...
Power systems are inherently graph-structured: buses as nodes, transmission lines as edges, with attributes like voltage, power flows, and topology. Traditional machine learning struggles with this ...
The mechanical behavior of viscoelastic materials is influenced, among other factors, by parameters like time and temperature. The present paper proposes a methodology for a thermorheologically and ...
Deep Neural Network (DNN)–based stereo models have become essential for depth estimation because they overcome many of the fundamental limitations of classical and geometry-based stereo algorithms.
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