65 citations · 201 across the 13 of their papers we have counts for
Showing 2022Show all
2 papers · 1 filter
cs.LG2022
Bayesian autoencoders with uncertainty quantification: Towards trustworthy anomaly detection
Bang Xiang Yong, Alexandra Brintrup
Despite numerous studies of deep autoencoders (AEs) for unsupervised anomaly detection, AEs still lack a way to express uncertainty in their predictions, crucial for ensuring safe…
cs.LG2022
Do autoencoders need a bottleneck for anomaly detection?
Bang Xiang Yong, Alexandra Brintrup
A common belief in designing deep autoencoders (AEs), a type of unsupervised neural network, is that a bottleneck is required to prevent learning the identity function. Learning th…