82 citations · 115 across the 8 of their papers we have counts for
4 papers · 1 filter
GP-ConvCNP: Better Generalization for Convolutional Conditional Neural Processes on Time Series Data
Jens Petersen, Gregor Köhler, David Zimmerer +3
Neural Processes (NPs) are a family of conditional generative models that are able to model a distribution over functions, in a way that allows them to perform predictions at test…
High- and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection
David Zimmerer, Jens Petersen, Klaus Maier-Hein
Variational Auto-Encoders have often been used for unsupervised pretraining, feature extraction and out-of-distribution and anomaly detection in the medical field. However, VAEs of…
Unsupervised Anomaly Localization using Variational Auto-Encoders
David Zimmerer, Fabian Isensee, Jens Petersen +2
An assumption-free automatic check of medical images for potentially overseen anomalies would be a valuable assistance for a radiologist. Deep learning and especially Variational A…
Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection
David Zimmerer, Simon A. A. Kohl, Jens Petersen +2
Unsupervised learning can leverage large-scale data sources without the need for annotations. In this context, deep learning-based auto encoders have shown great potential in detec…