Probabilistic Models with Deep Neural Networks

Probabilistic Models with Deep Neural Networks

Recent advances in statistical inference have significantly expanded the toolbox of probabilistic modeling. Historically, probabilistic modeling has been constrained to very restricted model classes, where exact or approximate probabilistic inference is feasible. However, developments in variational...

Full description

Bibliographic Details
Main Authors: Masegosa Arredondo, Andrés Ramón, Cabañas de Paz, Rafael, Langseth, Helge, Nielsen, Thomas Dyhre, Salmerón Cerdán, Antonio
Format: info:eu-repo/semantics/article
Language:English
Published: MDPI 2021
Subjects:
deep probabilistic modeling
variational inference
neural networks
latent variable models
Bayesian learning
Online Access:http://hdl.handle.net/10835/9516

Internet

http://hdl.handle.net/10835/9516

Similar Items