A Survey on Variational Autoencoders in Recommender Systems
S Liang, Z Pan, wei liu, J Yin, M de Rijke - ACM Computing Surveys, 2024 - dl.acm.org
Recommender systems have become an important instrument to connect people to
information. Sparse, complex, and rapidly growing data presents new challenges to …
information. Sparse, complex, and rapidly growing data presents new challenges to …
Evaluating open-domain dialogues in latent space with next sentence prediction and mutual information
The long-standing one-to-many issue of the open-domain dialogues poses significant
challenges for automatic evaluation methods, ie, there may be multiple suitable responses …
challenges for automatic evaluation methods, ie, there may be multiple suitable responses …
Variational image registration with learned prior using multi-stage VAEs
Y Hua, K Xu, X Yang - Computers in Biology and Medicine, 2024 - Elsevier
Abstract Variational Autoencoders (VAEs) are an efficient variational inference technique
coupled with the generated network. Due to the uncertainty provided by variational …
coupled with the generated network. Due to the uncertainty provided by variational …
Artificial Intelligence For Factory Automation–Anomaly Detection For Quality Control
A Palanisamy Chandrasekaran - 2024 - diva-portal.org
This thesis explores the application of artificial intelligence, specifically using autoencoder
(AE) and variational autoencoder (VAE), for anomaly detection, when dealing with data …
(AE) and variational autoencoder (VAE), for anomaly detection, when dealing with data …