Centre Inria de l'Université de Rennes

Efficiency of Estimating Smooth Functions of Parameters in Rare-Event Contexts

Consider an estimand that is a known smooth function of an unknown vector of parameters, such as means, probabilities, quantiles, etc. Some but not necessarily all of the parameters relate to rare events, which typically make them difficult to estimate with naive Monte Carlo, so...

Unsupervised deep generative models for anomaly detection in neuroimaging: A systematic scoping review

Unsupervised anomaly detection (UAD) based on deep generative modelling has been increasingly investigated for identifying pathological brain abnormalities without requiring voxel-level annotations. By learning the distribution of healthy anatomy and generating pseudo-healthy rec...