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

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

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

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.