Tensor math is at the heart of linear algebra and has applications in various fields from materials science to machine learning itself.

Familiarity with linear algebra is expected. In addition, students should have taken a proof-based course such as CS 212 or Math 300. Tensors, or multiindexed arrays, generalize matrices (two ...

We need to develop new computational techniques for understanding tensors, as their applications continue to grow across engineering and the sciences. This opportunity gives Grochow a pathway to ...

Ready to unlock your full math potential? 🎓Follow for clear, fun, and easy-to-follow lessons that will boost your skills, ...

When DL theorists saw the development of the GPU, they quickly adopted it for the clear acceleration of tensor math. GPUs are critical to the growth of the ML industry, driving training and ...

Applied mathematicians and computational scientists are on the front lines of scientific and technological advancement. A strong background in computer modeling helps you develop complex models that ...

It is shown how one may use operator space tensor product to define Hopf algebraic operations on the preduals of Hopf von Neumann algebras. A careful discussion of the extended Haagerup tensor product ...