Tensor network methods provide a structured approach to representing and manipulating high-dimensional data by decomposing global information into interconnected low-rank tensors. Originating in the ...

Deep machine learning has achieved remarkable success in various fields of artificial intelligence, but achieving both high interpretability and high efficiency simultaneously remains a critical ...

The complex spatiotemporal dynamics of neurons encompass a wealth of information relevant to perception and decision-making, making the decoding of neural activity a central focus in neuroscience ...

Sam Mugel, Ph.D., is the CTO of Multiverse Computing, a global leader in developing value-driven quantum solutions for businesses. Carbon emissions continue to plague the planet’s climate and endanger ...

Dan Fleisch briefly explains some vector and tensor concepts from A Student’s Guide to Vectors and Tensors. In the field of machine learning, tensors are used as representations for many applications, ...