Useful links
============

- The github repository `teneva_jax <https://github.com/AndreiChertkov/teneva_jax>`_ with the fast `jax` version of the `teneva` code.

- The github repository `teneva_bm <https://github.com/AndreiChertkov/teneva_bm>`_ with benchmarks library for testing multidimensional approximation and optimization methods.

- The github repository `teneva_opti <https://github.com/AndreiChertkov/teneva_opti>`_ with wrapper for various optimizers adapted to work with benchmarks from `teneva_bm`.

- The github repository `ttopt <https://github.com/AndreiChertkov/ttopt>`_ with the gradient-free optimization method `TTOpt` for multivariable functions based on the TT-format and maximal-volume principle (see also `NeurIPS-2022 paper <https://proceedings.neurips.cc/paper_files/paper/2022/hash/a730abbcd6cf4a371ca9545db5922442-Abstract-Conference.html>`_).

- The github repository `PROTES <https://github.com/anabatsh/PROTES>`_ with the optimization method `PROTES` (PRobability Optimizer with TEnsor Sampling) for derivative-free optimization of the multidimensional arrays and discretized multivariate functions based on the TT-format (see also `arxiv paper <https://arxiv.org/pdf/2301.12162.pdf>`_).

- The github repository `Constructive-TT <https://github.com/G-Ryzhakov/Constructive-TT>`_ with the method for constructive TT-representation of the tensors given as index interaction functions (see also `ICLR-2023 paper <https://openreview.net/forum?id=yLzLfM-Esnu>`_).

- Paper `Tensor train decomposition <https://sites.pitt.edu/~sjh95/related_papers/tensor_train_decomposition.pdf>`_, in which the TT-decomposition is presented and the main its properties are described.

- Dissertation work `Computational tensor methods and their applications <https://disk.yandex.ru/i/JEQXcFQlGuntyQ>`_ (in Russian only), in which the TT-decomposition is proposed and all its properties are described in detail.

- Dissertation work `Tensor methods for multidimensional differential equations <https://www.hse.ru/sci/diss/847453144>`_ (in Russian only), which presents various new algorithms in the TT-format for problems of multidimensional approximation, optimization and solution of differential equations.