Alternatives and similar repositories for neurips2021_multimodal_topmethods

Users that are interested in neurips2021_multimodal_topmethods are comparing it to the libraries listed below

• hui2000ji / scETM
  A generative topic model that facilitates integrative analysis of large-scale single-cell RNA sequencing data.
  ☆53Updated 3 years ago
• xiaoyeye / GCNG
  using graph convolutional neural network and spaital transcriptomics data to infer cell-cell interactions
  ☆56Updated 4 years ago
• ruiyi-zhang / scPretrain
  scPretrain: Multi-task self-supervised learning for cell type classification
  ☆23Updated 3 years ago
• snap-stanford / mars
  Discovering novel cell types across heterogenous single-cell experiments
  ☆123Updated 2 years ago
• caokai1073 / uniPort
  a unified single-cell data integration framework by optimal transport
  ☆35Updated last year
• HantaoShu / DeepSEM
  ☆85Updated 2 years ago
• welch-lab / PerturbNet
  PerturbNet is a deep generative model that can predict the distribution of cell states induced by chemical or genetic perturbation
  ☆48Updated 2 months ago
• biomed-AI / GraphSCI
  Imputing Single-cell RNA-seq data by combining Graph Convolution and Autoencoder Neural Networks
  ☆19Updated last year
• ml4bio / CLEAR
  CLEAR: Self-supervised contrastive learning for integrative single-cell RNA-seq data analysis
  ☆34Updated 2 years ago
• OmicsML / scDiff
  scDiff: A General Single-Cell Analysis Framework via Conditional Diffusion Generative Models
  ☆30Updated last year
• kodaim1115 / scMM
  ☆18Updated 4 years ago
• bunnech / cellot
  Learning Single-Cell Perturbation Responses using Neural Optimal Transport
  ☆146Updated 11 months ago
• OSU-BMBL / deepmaps
  Single-cell biological network inference using a heterogeneous graph transformer
  ☆76Updated 7 months ago
• OmicsML / scMoFormer
  Single-Cell Multimodal Prediction via Transformer
  ☆28Updated last year
• theislab / cpa
  The Compositional Perturbation Autoencoder (CPA) is a deep generative framework to learn effects of perturbations at the single-cell leve…
  ☆112Updated last year
• Genentech / sVAE
  ☆63Updated 2 years ago
• alexw16 / gridnet
  ☆15Updated 3 months ago
• juexinwang / scGNN
  scGNN (single cell graph neural networks) for single cell clustering and imputation using graph neural networks
  ☆151Updated last year
• yulun-rayn / graphVCI
  Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information (ICLR 2023)
  ☆19Updated 3 months ago
• openproblems-bio / neurips2021-notebooks
  ☆30Updated 3 years ago
• yhr91 / GEARS_misc
  ☆22Updated 11 months ago
• ZixiangLuo1161 / scGAE
  single-cell graph autoencoder
  ☆24Updated 3 years ago
• theislab / chemCPA
  Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
  ☆124Updated 8 months ago
• aaronwtr / PertEval
  Evaluation suite for transcriptomic perturbation effect prediction models. Includes support for single-cell foundation models.
  ☆26Updated 2 months ago
• rvinas / HYFA
  Hypergraph Factorisation
  ☆26Updated 10 months ago
• nitzanlab / biolord
  ☆84Updated last year
• microsoft / zero-shot-scfoundation
  ☆72Updated last year
• openproblems-bio / neurips2021_multimodal_viash
  ☆18Updated 3 years ago
• davidbuterez / CellVGAE
  An unsupervised scRNA-seq analysis workflow with graph attention networks
  ☆26Updated 2 years ago
• theislab / scgen-reproducibility
  ☆28Updated 5 years ago