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, ...
“Next Gen NYC” is back and it’s anything but chill. The pace is faster, the hustle is louder, and for this New York City crew, life in the city that never sleeps is a full-on reality check. Everyone’s ...
Abstract: In recent years, deep learning-based methods have attracted much attention and achieved remarkable results for intelligent fault diagnosis of rotating machinery. However, in many actual ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results