Parameter tuning is a key part of dimensionality reduction via deep variational autoencoders for single cell RNA transcriptomics

Antzeko izenburuak

• A deep adversarial variational autoencoder model for dimensionality reduction in single-cell RNA sequencing analysis
  nork: Lin, Eugene, et al.
  Argitaratua: (2020)
• Tuning parameters of dimensionality reduction methods for single-cell RNA-seq analysis
  nork: Raimundo, Felix, et al.
  Argitaratua: (2020)
• Extracting a biologically relevant latent space from cancer transcriptomes with variational autoencoders
  nork: Way, Gregory P., et al.
  Argitaratua: (2018)
• scVAEDer: integrating deep diffusion models and variational autoencoders for single-cell transcriptomics analysis
  nork: Mehrshad Sadria, et al.
  Argitaratua: (2025-03-01)
• VASC: Dimension Reduction and Visualization of Single-cell RNA-seq Data by Deep Variational Autoencoder
  nork: Wang, Dongfang, et al.
  Argitaratua: (2018)