Tensors play a pivotal role in AI and deep learning systems, and share a common heritage with both physics and advanced mathematics. All of which makes it extremely difficult to lock down a ...

Tensors are simply mathematical objects that can be used to describe physical properties, just like scalars and vectors. In fact tensors are merely a generalisation of scalars and vectors; a scalar is ...

Tomographic measurement of dielectric tensors at optical frequency. Nature Materials, 2022; 21 (3): 317 DOI: 10.1038/s41563-022-01202-8 ...

Tensors, or multiindexed arrays, generalize matrices (two dimensional) to three dimensions and beyond. Due to the great ability of tensors to model higher-order data and nonlinear functions, tensor ...

A symmetric tensor is completely positive (CP) if it is a sum of tensor powers of nonnegative vectors. This paper characterizes completely positive binary tensors. We show that a binary tensor is ...

Because isomorphic tensors present differently, discovering that they're secretly the same can actually be quite difficult. Grochow's project will allow him to move back and forth between creating new ...

The tensors considered in this paper are the linear relationships between certain pairs of physical vector quantities which may be described by $3 \times 3$ symmetric matrices. Such a linear ...

Tensors are data structures used by machine-learning models. Both of the new methods seek to efficiently exploit what's known as sparsity -- zero values -- in the tensors.