Learning Energy-Based Models in High-Dimensional Spaces with Multiscale Denoising-Score Matching

Energy-based models (EBMs) assign an unnormalized log probability to data samples. This functionality has a variety of applications, such as sample synthesis, data denoising, sample restoration, outlier detection, Bayesian reasoning and many more. But, the training of EBMs using standard maximum lik...

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Detalles Bibliográficos
Autores principales: Li, Zengyi, Chen, Yubei, Sommer, Friedrich T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606347/
https://www.ncbi.nlm.nih.gov/pubmed/37895489
http://dx.doi.org/10.3390/e25101367

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10606347/
https://www.ncbi.nlm.nih.gov/pubmed/37895489
http://dx.doi.org/10.3390/e25101367

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