openproblems-bio / neurips2021_multimodal_topmethodsLinks
☆81Updated 3 years ago
Alternatives and similar repositories for neurips2021_multimodal_topmethods
Users that are interested in neurips2021_multimodal_topmethods are comparing it to the libraries listed below
Sorting:
- A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.☆52Updated 4 years ago
- Discovering novel cell types across heterogenous single-cell experiments☆123Updated 3 years ago
- using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions☆55Updated 4 years ago
- scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks☆155Updated last year
- ☆66Updated 2 years ago
- scPretrain: Multi-task self-supervised learning for cell type classification☆23Updated 4 years ago
- ☆30Updated 4 years ago
- ☆90Updated 2 years ago
- Single-cell biological network inference using a heterogeneous graph transformer☆76Updated 11 months ago
- ☆19Updated 4 years ago
- ☆15Updated 7 months ago
- a unified single-cell data integration framework by optimal transport☆36Updated last year
- CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis☆35Updated 3 years ago
- ☆18Updated 4 years ago
- Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)☆19Updated 7 months ago
- resVAE is a restricted latent variational autoencoder that we wrote to uncover hidden structures in gene expression data, especially usin…☆12Updated 3 years ago
- federated learning with tabular learning☆26Updated 11 months ago
- Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks☆20Updated last year
- Learning Single-Cell Perturbation Responses using Neural Optimal Transport☆157Updated last year
- ☆70Updated 6 months ago
- Single-Cell Multimodal Prediction via Transformer☆28Updated 2 years ago
- The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…☆134Updated last year
- covolutional neural network based coexpression analysis☆79Updated 5 years ago
- Hypergraph Factorisation☆26Updated last year
- single-cell graph autoencoder☆25Updated 4 years ago
- scDiff: A General Single-Cell Analysis Framework via Conditional Diffusion Generative Models☆32Updated last year
- CellBox: Interpretable Machine Learning for Perturbation Biology☆56Updated 2 years ago
- An explainable multi-omics graph integration method based on graph convolutional networks to predict cancer genes.☆160Updated 3 years ago
- ☆35Updated 3 years ago
- A simulator for single-cell expression data guided by gene regulatory networks☆73Updated last year