A multi-encoder variational autoencoder controls multiple transformational features in single-cell image analysis
Image-based cell phenoty** relies on quantitative measurements as encoded
representations of cells; however, defining suitable representations that capture complex …
representations of cells; however, defining suitable representations that capture complex …
MichiGAN: sampling from disentangled representations of single-cell data using generative adversarial networks
Deep generative models such as variational autoencoders (VAEs) and generative
adversarial networks (GANs) generate and manipulate high-dimensional images. We …
adversarial networks (GANs) generate and manipulate high-dimensional images. We …
Me-vae: Multi-encoder variational autoencoder for controlling multiple transformational features in single cell image analysis
Image-based cell phenoty** relies on quantitative measurements as encoded
representations of cells; however, defining suitable representations that capture complex …
representations of cells; however, defining suitable representations that capture complex …
Deep Generative Models for Single-Cell Perturbation Experiments
H Yu - 2022 - deepblue.lib.umich.edu
Recent developments in deep learning have enabled generation of novel and realistic
images or sentences from low-dimensional representations. In addition, a revolution in …
images or sentences from low-dimensional representations. In addition, a revolution in …
[PDF][PDF] ME-VAE: Multi-Encoder Variational AutoEncoder for Controlling Multiple
Image-based cell phenoty** relies on quantitative measurements as encoded
representations of cells; however, defining suitable representations that capture complex …
representations of cells; however, defining suitable representations that capture complex …