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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

168,657 papers · 148 categories

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7 results for “Multiomics”

Graph Canonical Correlation Analysisstat.ML

Graph Canonical Correlation Analysis improves CCA for multiomics datasets.

problem Limited ability of conventional CCA methods to incorporate structured patterns in cross-correlation matrices.

method Graph Canonical Correlation Analysis (gCCA) calculates canonical correlations based on the graph structure of cross-correlation matrices.

result gCCA outperforms competing CCA methods in simulations and multiomics dataset analysis.

Canonical Correlation Analysis Graph Structure Multiomics Structured Patterns RNA-seq

2025-02-03abs ↗pdf ↗

Structured Transforms Across Spaces with Cost-Regularized Optimal Transportcs.LG

A new method matches measures across different spaces using cost-regularized optimal transport.

problem Matching measures in different spaces without aligned data.

method Cost-regularized optimal transport formulation to match measures across two Euclidean spaces.

result Demonstrated applicability to single-cell spatial transcriptomics/multiomics matching tasks.

optimal transport cost regularization multiomics spatial transcriptomics Euclidean spaces

2023-11-09abs ↗pdf ↗

Extrapolated cross-validation for randomized ensemblesstat.ME

ECV method optimizes ensemble parameters for randomized ensembles.

problem Efficient tuning of ensemble parameters in randomized ensembles.

method ECV (Extrapolated Cross-Validation) method for tuning ensemble and subsample sizes.

result ECV yields δ-optimal ensembles for squared prediction risk.

ensemble methods cross-validation randomized ensembles prediction risk surface protein abundances

2023-02-27abs ↗pdf ↗

Cooperative learning for multiview analysisstat.ME

A new method for combining multiple data views in supervised learning.

problem Combining multiple data views in supervised learning, especially in biology and medicine.

method Cooperative learning combines squared error loss with an agreement penalty to encourage predictions from different data views to agree.

result Cooperative learning achieves higher predictive accuracy on simulated and real multiomics data.

cooperative learning multiview analysis supervised learning omics data agreement penalty

2021-12-23abs ↗pdf ↗

scICML: Information-theoretic Co-clustering-based Multi-view Learning for the Integrative Analysis of Single-cell Multi-omics datastat.ML

scICML integrates multi-omics data from single cells using co-clustering.

problem High noise and sparsity in multi-omics data from single cells.

method Information-theoretic co-clustering-based multi-view learning.

result Improves clustering performance and provides biological insights.

co-clustering multi-view learning single-cell omics information theory multiomics

2022-05-19abs ↗pdf ↗

Simple and Scalable Algorithms for Cluster-Aware Precision Medicinecs.LG

AI-enabled precision medicine promises a transformational improvement in healthcare outcomes by enabling data-driven personalized diagnosis, prognosis, and treatment. However, the well-known "curse of dimensionality" and the clustered structure of biomedical data together interact to present a joint challenge in the hi…

2022-11-29abs ↗pdf ↗

A deep learning pipeline for cross-sectional and longitudinal multiview data integrationcs.LG

Pipeline integrates cross-sectional and longitudinal multi-omics data for IBD research.

problem Integrating diverse data types from the same individuals for disease understanding.

method Statistical and deep learning methods for variable selection, feature extraction, and joint integration.

result Identified microbial pathways, metabolites, and genes discriminating IBD status.

deep learning multiomics IBD cross-sectional longitudinal

2023-12-02abs ↗pdf ↗