6 papers
Variational Low-rank Tensor Decomposition for Multisubject Spatiotemporal Data Analysis
Laura M. Montaldo, Ricardo A. Borsoi, Sebastian Miron +1
Modeling shared and subject-specific structure in multisubject spatiotemporal data remains challenging, particularly in neuroimaging, where both spatial and temporal patterns exhib…
Isolating Nonlinear Independent Sources in fMRI with -TCVAE Models
Qiang Li, Shujian Yu, Jesus Malo +3
Learning meaningful latent representations from nonlinear fMRI data remains a fundamental challenge in neuroimaging analysis. Traditional independent component analysis, widely use…
Deep Deterministic Nonlinear ICA via Total Correlation Minimization with Matrix-Based Entropy Functional
Qiang Li, Shujian Yu, Liang Ma +4
Blind source separation, particularly through independent component analysis (ICA), is widely utilized across various signal processing domains for disentangling underlying compone…
Personalized Coupled Tensor Decomposition for Multimodal Data Fusion: Uniqueness and Algorithms
Ricardo Augusto Borsoi, Konstantin Usevich, David Brie +1
Coupled tensor decompositions (CTDs) perform data fusion by linking factors from different datasets. Although many CTDs have been already proposed, current works do not address imp…
An Effective Iterative Solution for Independent Vector Analysis with Convergence Guarantees
Clément Cosserat, Ben Gabrielson, Emilie Chouzenoux +2
Independent vector analysis (IVA) is an attractive solution to address the problem of joint blind source separation (JBSS), that is, the simultaneous extraction of latent sources f…
Copula-Linked Parallel ICA: A Method for Coupling Structural and Functional MRI brain Networks
Oktay Agcaoglu, Rogers F. Silva, Deniz Alacam +3
Different brain imaging modalities offer unique insights into brain function and structure. Combining them enhances our understanding of neural mechanisms. Prior multimodal studies…