andrewcharlesjones / pcpcaLinks
Probabilistic contrastive principal component analysis (PCPCA)
☆24Updated 3 years ago
Alternatives and similar repositories for pcpca
Users that are interested in pcpca are comparing it to the libraries listed below
Sorting:
- generalized principal component analysis (GLM-PCA) implemented in python☆59Updated 4 years ago
- A Library for Denoising Single-Cell Data with Random Matrix Theory☆37Updated 2 years ago
- pyGPCCA - python GPCCA: Generalized Perron Cluster Cluster Analysis package to coarse-grain reversible and non-reversible Markov state mo…☆22Updated 5 months ago
- ☆10Updated last year
- This Python package will allow you to replicate the experiments from our research on applying Optimal Transport as a similarity metric in…☆42Updated 2 years ago
- A Python package for General Graphical Lasso computation☆37Updated 6 months ago
- ☆11Updated 3 months ago
- A versatile interface to the knockoff methodology.☆26Updated 3 years ago
- A spectral method for assessing and combining multiple data visualizations☆50Updated 2 years ago
- PyTorch implementation of BasisVAE: Translation-invariant feature-level clustering with Variational Autoencoders☆42Updated 5 years ago
- Bootstrap Elastic net regression from Time Series is a vector-autoregressive approach to causal inference from gene expression time serie…☆20Updated 2 years ago
- Contrastive Poisson latent variable models (CPLVMs)☆11Updated 3 years ago
- Multilayer modelling of the human transcriptome and biological mechanisms of complex diseases and traits☆11Updated 4 years ago
- ☆63Updated 2 years ago
- Gaussian process regression package for counts data with negative binomial and zero-inflated negative binomial likelihoods☆22Updated 6 months ago
- Creating multi-resolution embeddings and clusters from high dimensional data☆55Updated 11 months ago
- Code for the paper "End-to-end training of deep probabilistic CCA on paired biomedical observations".☆28Updated 4 years ago
- Branching Gaussian process☆30Updated 2 years ago
- Latent spaces for single cells☆21Updated last year
- ☆12Updated 3 years ago
- Testing if UMAP/tSNE overfit their intrinsic dimensionality☆15Updated 2 years ago
- ☆16Updated 3 years ago
- The art of using t-SNE for single-cell transcriptomics☆127Updated 9 months ago
- Simulating single-cell data using gene regulatory networks 📠☆75Updated last year
- Git Repo for simulating Boolean Models☆35Updated last year
- Conditional out-of-distribution prediction☆63Updated last year
- Initialization is critical for preserving global data structure in both t-SNE and UMAP☆23Updated 4 years ago
- Use LSTM neural network for 1D distributional data prediction☆22Updated 2 years ago
- Systematically learn and evaluate manifolds from high-dimensional data☆101Updated this week
- Dynamic inference from single-cell snapshots by optimal transport☆19Updated last year