swMATH ID: 35476
Software Authors: Rafael Ballester-Ripoll
Description: tntorch - Tensor Network Learning with PyTorch. This is a PyTorch-powered library for tensor modeling and learning that features transparent support for the tensor train (TT) model, CANDECOMP/PARAFAC (CP), the Tucker model, and more. Supported operations (CPU and GPU) include: Basic and fancy indexing of tensors, broadcasting, assignment, etc.; Tensor decomposition and reconstruction; Element-wise and tensor-tensor arithmetics; Building tensors from black-box functions using cross-approximation; Statistics and sensitivity analysis; Optimization using autodifferentiation, useful for e.g. regression or classification; Misc. operations on tensors: stacking, unfolding, sampling, derivating, etc.
Homepage: https://tntorch.readthedocs.io/en/latest/
Source Code: https://github.com/rballester/tntorch
Dependencies: PyTorch
Related Software: TensorFlow; t3f; PyTorch; Scikit-TT; GitHub; NumPy; TensorLy; LAPACK; Algorithm 844; likwid; MKL; Eigen; TensorNetwork; TensorD; TedNet; mps; libtt; MPyS; mpnum; evoMPS
Cited in: 1 Publication

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