Poster

tntorch: Tensor Network Learning with PyTorch

Mikhail Usvyatsov · Rafael Ballester-Ripoll · Konrad Schindler

Keywords: [ JMLR ] [ Journal Track ]

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Spotlight presentation: Lightning Talks 1A-1
Tue 6 Dec 9 a.m. PST — 9:15 a.m. PST

Abstract:

We present tntorch, a tensor learning framework that supports multiple decompositions (including Candecomp/Parafac, Tucker, and Tensor Train) under a unified interface. With our library, the user can learn and handle low-rank tensors with automatic differentiation, seamless GPU support, and the convenience of PyTorch's API. Besides decomposition algorithms, tntorch implements differentiable tensor algebra, rank truncation, cross-approximation, batch processing, comprehensive tensor arithmetics, and more.

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