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tntorch: Tensor Network Learning with PyTorch
Mikhail Usvyatsov · Rafael Ballester-Ripoll · Konrad Schindler

Tue Dec 06 09:00 AM -- 11:00 AM (PST) @
in Lightning Talks 1A-1 »

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.

Keywords: Journal Track · JMLR

Author Information

Mikhail Usvyatsov (ETH Zürich)
Rafael Ballester-Ripoll
Konrad Schindler (ETH Zürich)

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