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20222026
most citedEvaluation of pseudo-healthy image reconstruction for anomaly detection with deep generative models: Application to brain FDG PET

8 citations · 15 across the 7 of their papers we have counts for

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2 papers · 1 filter

eess.IV2023★ 3 cited

Leveraging healthy population variability in deep learning unsupervised anomaly detection in brain FDG PET

Maëlys Solal, Ravi Hassanaly, Ninon Burgos

Unsupervised anomaly detection is a popular approach for the analysis of neuroimaging data as it allows to identify a wide variety of anomalies from unlabelled data. It relies on b…

physics.data-an2023

Using uncertainty-aware machine learning models to study aerosol-cloud interactions

Maëlys Solal, Andrew Jesson, Yarin Gal +1

Aerosol-cloud interactions (ACI) include various effects that result from aerosols entering a cloud, and affecting cloud properties. In general, an increase in aerosol concentratio…