ArticlebioRxiv : the preprint server for biology2025
Fast Probabilistic Whitening Transformation for Ultra-High Dimensional Genetic Data.
Article in bioRxiv : the preprint server for biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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Authors and funding
4 authors.
Funding
Abstract
Statistical methods often make assumptions about independence between the samples or features of a dataset. Yet correlation structure is ubiquitous in real data, so these assumptions are often not met in practice. Whitening transformations are widely applied to remove this correlation structure. Existing approaches to whitening are based on standard linear algebra, rather than a probabilistic model, and application to high dimensional datasets with
Identifiers
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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 Socratic graph.