Tensors provide a consistent map of real world elements that the neural network can understand. For instance, in image recognition, tensors are used to represent pixel data as matrices, ...

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 ...

We always enjoy [FloatHeadPhysics] explaining any math or physics topic. We don’t know if he’s acting or not, but he seems genuinely excited about every topic he covers, and it is ...

It is useful to understand Tensors, Tensorflow, and TPU (Tensor processing units). Tensors are simply mathematical objects that can be used to describe physical properties, just like scalars and ...

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.

Such tensors are very small in size, so when handling actual data sets, the cores would crunch through little blocks of larger matrices, building up the final answer. Less than a year later ...

A research team reported the direct measurement of dielectric tensors of anisotropic structures including the spatial variations of principal refractive indices and directors. The group also ...

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 ...