A framework based on the tensor train decomposition for working with multivariate functions and multidimensional arrays

Gradient-free optimization method for multivariable functions based on the low rank tensor train (TT) format and maximal-volume principle.

[SP 2024] A Novel Recursive Least-Squares Adaptive Method For Streaming Tensor-Train Decomposition With Incomplete Observations. In Elsevier Signal Processing, 2024.

[IEEE ICASSP 2021] "A fast randomized adaptive CP decomposition for streaming tensors". In 46th IEEE International Conference on Acoustics, Speech, & Signal Processing, 2021.

A Python Package for Advanced Tensor Learning

[Patterns 2023] Tracking Online Low-Rank Approximations of Higher-Order Incomplete Streaming Tensors. In Patterns (Cell Press) 2023.

Coupled matrix-tensor factorization for integrating EEG and ffMRI on the brain cortical surface with source reconstruction

[EUSIPCO 2022] "Robust Tensor Tracking With Missing Data Under Tensor-Train Format". In 30th European Signal Processing Conference, 2022.

This repository contains the software used in the paper "Empirical Evaluation of Four Tensor Decomposition Algorithms" (see four-tensor-decompositions.pdf).

Penalized tensor regression for whole brain connectivity.

Tensor Granger Causality with t-Product Algorithm

Model identifiability pipeline using surrogate models trained on a latent space extracted by tensor decompositions.