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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.

168,695 papers · 148 categories

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5 results for “scVI”

Benchmarking Transcriptomics Foundation Models for Perturbation Analysis : one PCA still rules them allcs.LG

This study benchmarks transcriptomics models for perturbation analysis, finding scVI and PCA superior.

problem Limited evaluation of transcriptomics foundation models for perturbation analysis.

method Developed a novel evaluation framework using diverse public datasets from different sequencing techniques and cell lines.

result scVI and PCA identified as superior models for understanding biological perturbations.

transcriptomics foundation models perturbation analysis scVI PCA

2024-10-17abs ↗pdf ↗

Scalable Amortized GPLVMs for Single Cell Transcriptomics Datastat.ML

Improved GPLVM model for single-cell RNA-seq data.

problem Lack of effective scalable models for clustering cell types in large-scale single-cell RNA-seq data.

method Introduces amortized stochastic variational Bayesian GPLVM (BGPLVM) tailored for single-cell RNA-seq.

result Matches the performance of scVI on synthetic and real-world datasets and reveals more interpretable latent structures.

GPLVM single-cell RNA-seq dimensionality reduction cell clustering variational inference

2024-05-06abs ↗pdf ↗

A Tutorial on the Mathematical Model of Single Cell Variational Inferenceq-bio.OT

Tutorial on using neural networks for single cell data analysis.

problem Handling large sequencing datasets efficiently.

method Single cell variational inference using variational auto-encoder.

result Model learns data distribution for insights.

single cell analysis variational auto-encoder neural networks sequencing data data efficiency

2021-01-03abs ↗pdf ↗

The VampPrior Mixture Modelcs.LG

VampPrior Mixture Model improves clustering in DLVMs.

problem Simplicity of standard priors in DLVMs leads to poor clustering performance.

method Leverages VampPrior concepts to fit a Bayesian GMM prior in a VAE.

result VMM achieves highly competitive clustering performance on benchmark datasets.

VampPrior Bayesian GMM Deep Latent Variable Models Clustering Autoencoders

2024-02-06abs ↗pdf ↗

Donor-Aware scRNA-seq Benchmarks for IBD Classificationq-bio.QM

Donor-aware scRNA-seq benchmarks improve classification accuracy in inflammatory bowel disease.

problem Influenza disease classification from scRNA-seq data is prone to donor-level confounding.

method Developed and evaluated three feature representations across two IBD cohorts.

result Compartment-stratified CLR composition and GatedStructuralCFN embeddings outperform linear models in classification accuracy.

scRNA-seq IBD Donor-aware Cross-validation Feature embeddings

2026-05-05abs ↗pdf ↗