In: Monatshefte für Mathematik, 2015, vol. 178, no. 2, p. 171-190
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In: International Journal of Computer Assisted Radiology and Surgery, 2015, vol. 10, no. 7, p. 1097-1107
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In: International Journal of Computer Assisted Radiology and Surgery, 2015, vol. 10, no. 6, p. 681-693
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In: Numerical Algorithms, 2015, vol. 69, no. 2, p. 455-469
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In: Frontiers in Genetics, 2020, vol. 11, p. -
Classification of histopathological images of cancer is challenging even for well- trained professionals, due to the fine-grained variability of the disease. Deep Convolutional Neural Networks (CNNs) showed great potential for classification of a number of the highly variable fine-grained objects. In this study, we introduce a Bilinear Convolutional Neural Networks (BCNNs) based deep learning...
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In: Entropy, 2019, vol. 21, no. 8, p. 758
Variational inference with a factorized Gaussian posterior estimate is a widely-used approach for learning parameters and hidden variables. Empirically, a regularizing effect can be observed that is poorly understood. In this work, we show how mean field inference improves generalization by limiting mutual information between learned parameters and the data through noise. We quantify a...
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In: International Journal of Computer Assisted Radiology and Surgery, 2014, vol. 9, no. 2, p. 165-176
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In: Journal of Time Series Econometrics, 2016, vol. 8, no. 2, p. 155-192
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In: International Journal of Computer Assisted Radiology and Surgery, 2014, vol. 9, no. 1, p. 11-20
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In: Journal of Mathematical Imaging and Vision, 2014, vol. 50, no. 3, p. 246-260
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