Description
Tensor-train numerical methods can be used from Python for high-dimensional scientific computing. This library implements TT-Toolbox-style operations for compressed tensors, helping researchers experiment with tensor decompositions and related algorithms.
It is imported by scripts, notebooks, or scientific applications rather than opened as a standalone app. Results and performance depend on the caller data and numerical assumptions, so research workflows should validate outputs.