ArticleIEEE sensors letters2019
ICA and IVA for Data Fusion: An Overview and a New Approach Based on Disjoint Subspaces.
Article in IEEE sensors letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
13 citing papers in PubMed.
- Fusion of Multi-Task fMRI Data: Guided Solutions for IVA and Transposed IVA.Sensors (Basel, Switzerland) · 2026Article
- aNy-way ICA and its application to estimate cortico-thalamo-cerebellar functional links in schizophrenia.bioRxiv : the preprint server for biology · 2025Article
- Independent Vector Analysis for Feature Extraction in Motor Imagery Classification.Sensors (Basel, Switzerland) · 2024Article
- Multimodal active subspace analysis for computing assessment oriented subspaces from neuroimaging data.Journal of neuroscience methods · 2024Article
- Exploring Neural Mechanisms of Reward Processing Using Coupled Matrix Tensor Factorization: A Simultaneous EEG-fMRI Investigation.Brain sciences · 2023Article
- A Survey of Optimization Methods for Independent Vector Analysis in Audio Source Separation.Sensors (Basel, Switzerland) · 2023Review
- Data-driven multimodal fusion: approaches and applications in psychiatric research.Psychoradiology · 2023Review
- Heterogeneous data integration methods for patient similarity networks.Briefings in bioinformatics · 2022Review
- Reproducibility in Matrix and Tensor Decompositions: Focus on Model Match, Interpretability, and Uniqueness.IEEE signal processing magazine · 2022Article
- Early soft and flexible fusion of electroencephalography and functional magnetic resonance imaging via double coupled matrix tensor factorization for multisubject group analysis.Human brain mapping · 2022Article
- Association of Neuroimaging Data with Behavioral Variables: A Class of Multivariate Methods and Their Comparison Using Multi-Task FMRI Data.Sensors (Basel, Switzerland) · 2022Article
- Disjoint subspaces for common and distinct component analysis: Application to the fusion of multi-task FMRI data.Journal of neuroscience methods · 2021Article
- aNy-way Independent Component Analysis.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Data-driven methods have been very attractive for fusion of both multiset and multimodal data, in particular using matrix factorizations based on independent component analysis (ICA) and its extension to multiple datasets, independent vector analysis (IVA). This is primarily due to the fact that independence enables (essentially) unique decompositions under very general conditions and for a large class of signals, and
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.