Model Catalog
Review 23 single-cell analysis models across 6 categories, then open the benchmark details you need.
scVI
Single-cell Variational Inference for probabilistic analysis of single-cell gene expression data.
scGNN
Graph Neural Network for single-cell RNA-seq analysis with cell-cell interaction modeling.
SCALEX
Single-Cell ATLAS eXtender for batch-effect free integration of single-cell atlases.
Cell BLAST
Cell type annotation and reference search using deep generative models.
PeakVI
Probabilistic modeling of scATAC-seq data using variational inference.
PoissonVI
Poisson-based variational inference for count data in scATAC-seq.
scTour
Trajectory inference with optimal transport and neural ODE for single-cell data.
β-VAE
Disentangled representation learning with adjustable β constraint on KL divergence.
InfoVAE
Information maximizing variational autoencoder with MMD regularization.
TCVAE
Total correlation VAE for disentangled representation learning.
DIPVAE
Disentangled Inferred Prior VAE for learning disentangled representations.
GMVAE (PGM)
Gaussian Mixture VAE with probabilistic graphical model structure.
scGCC
Graph Contrastive Clustering for single-cell data analysis.
CLEAR
Contrastive Learning for scRNA-seq data with augmentation strategies.
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LAIOR Benchmarks
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Open LAIOR BenchmarksscCCVGBen
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