Cargando…
Topological magnetic structure generation using VAE-GAN hybrid model and discriminator-driven latent sampling
Recently, deep generative models using machine intelligence are widely utilized to investigate scientific systems by generating scientific data. In this study, we experiment with a hybrid model of a variational autoencoder (VAE) and a generative adversarial network (GAN) to generate a variety of pla...
Autores principales: | Park, S. M., Yoon, H. G., Lee, D. B., Choi, J. W., Kwon, H. Y., Won, C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10663506/ https://www.ncbi.nlm.nih.gov/pubmed/37989882 http://dx.doi.org/10.1038/s41598-023-47866-3 |
Ejemplares similares
-
LSTM-Based VAE-GAN for Time-Series Anomaly Detection
por: Niu, Zijian, et al.
Publicado: (2020) -
Fast simulation of the LHCb electromagnetic calorimeter response using VAEs and GANs
por: Sergeev, Fedor, et al.
Publicado: (2021) -
Using VAEs to Learn Latent Variables: Observations on Applications in
cryo-EM
por: Edelberg, Daniel G., et al.
Publicado: (2023) -
siVAE: interpretable deep generative models for single-cell transcriptomes
por: Choi, Yongin, et al.
Publicado: (2023) -
Conditional VAE in medical field
por: Zoccheddu, Sara
Publicado: (2023)