ArticleJournal of machine learning research : JMLR2016
Bayesian group factor analysis with structured sparsity.
Article in Journal of machine learning research : JMLR, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed.
- Simultaneous Representation Learning of Multi-Omics and Clinical Outcome Data via a Supervised Knowledge-Guided Bayesian Factor Model.Statistics in medicine · 2026Article
- Matching Criterion for Identifiability in Sparse Factor Analysis.Psychometrika · 2026Article
- Sparse Bayesian Group Factor Model for Feature Interactions in Multiple Count Tables Data.Journal of the American Statistical Association · 2025Article
- Interpretable spatially aware dimension reduction of spatial transcriptomics with STAMP.Nature methods · 2024Article
- Graph-guided Bayesian Factor Model for Integrative Analysis of Multi-modal Data with Noisy Network Information.Statistics in biosciences · 2024Article
- A Bayesian multivariate factor analysis model for causal inference using time-series observational data on mixed outcomes.Biostatistics (Oxford, England) · 2024Article
- Incorporating graph information in Bayesian factor analysis with robust and adaptive shrinkage priors.Biometrics · 2024Article
- SuSiE PCA: A scalable Bayesian variable selection technique for principal component analysis.iScience · 2023Article
- A Poisson reduced-rank regression model for association mapping in sequencing data.BMC bioinformatics · 2022Article
- SpaceX: gene co-expression network estimation for spatial transcriptomics.Bioinformatics (Oxford, England) · 2022Article
- Telescoping bimodal latent Dirichlet allocation to identify expression QTLs across tissues.Life science alliance · 2022Article
- A hierarchical Bayesian model to find brain-behaviour associations in incomplete data sets.NeuroImage · 2022Article
- Understanding the Molecular Drivers of Disease Heterogeneity in Crohn's Disease Using Multi-omic Data Integration and Network Analysis.Inflammatory bowel diseases · 2021Article
- Joint analysis of expression levels and histological images identifies genes associated with tissue morphology.Nature communications · 2021Article
- Modeling statistical dependencies in multi-region spike train data.Current opinion in neurobiology · 2020Review
- Sparse multi-output Gaussian processes for online medical time series prediction.BMC medical informatics and decision making · 2020Article
- Community detection in networks without observing edges.Science advances · 2020Article
- Multi-Omics Factor Analysis-a framework for unsupervised integration of multi-omics data sets.Molecular systems biology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Latent factor models are the canonical statistical tool for exploratory analyses of low-dimensional linear structure for a matrix of
Indexed as
Identifiers
40994559PMC12456737What OpenQuestion holds
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.