Mixture-of-Experts Variational Autoencoder for clustering and generating from similarity-based representations on single cell data.
Clustering high-dimensional data, such as images or biological measurements, is a long-standing problem and has been studied extensively. Recently, Deep Clustering has gained popularity due to its flexibility in fitting the specific peculiarities of complex data. Here we introduce the Mixture-of-Exp...
Guardado en:
Autores principales: | Andreas Kopf, Vincent Fortuin, Vignesh Ram Somnath, Manfred Claassen |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
Public Library of Science (PLoS)
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/ce2ae803ad064ff398d2f8cd15512672 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Convolutional Autoencoding and Gaussian Mixture Clustering for Unsupervised Beat-to-Beat Heart Rate Estimation of Electrocardiograms from Wearable Sensors
por: Jun Zhong, et al.
Publicado: (2021) -
FaceVAE: Generation of a 3D Geometric Object Using Variational Autoencoders
por: Sungsoo Park, et al.
Publicado: (2021) -
A DEEP AUTOENCODER-BASED REPRESENTATION FOR ARABIC TEXT CATEGORIZATION
por: Fatima-Zahra El-Alami, et al.
Publicado: (2020) -
Explore Protein Conformational Space With Variational Autoencoder
por: Hao Tian, et al.
Publicado: (2021) -
Conditional Variational Autoencoder for Learned Image Reconstruction
por: Chen Zhang, et al.
Publicado: (2021)