3 citations · 3 across the 12 of their papers we have counts for
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Stabilizing In-Context Multi-Source Domain Adaptation for Biomedical Images Through Controls
Ana Sanchez-Fernandez, Thomas Pinetz, Werner Zellinger +1
Biomedical imaging data presents enormous potential for deep learning models to predict invaluable properties, such as diseases and drug effects. However, unavoidable alterations o…
Stochastic Siamese MAE Pretraining for Longitudinal Medical Images
Taha Emre, Arunava Chakravarty, Thomas Pinetz +9
Temporally aware image representations are crucial for capturing disease progression in 3D volumes of longitudinal medical datasets. However, recent state-of-the-art self-supervise…
On the estimation of the Wasserstein distance in generative models
Thomas Pinetz, Daniel Soukup, Thomas Pock
Generative Adversarial Networks (GANs) have been used to model the underlying probability distribution of sample based datasets. GANs are notoriuos for training difficulties and th…