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Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts
Multimodal generative models should be able to learn a meaningful latent...
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Lung Segmentation from Chest X-rays using Variational Data Imputation
Pulmonary opacification is the inflammation in the lungs caused by many ...
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The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up
We present the findings of "The Alzheimer's Disease Prediction Of Longit...
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On the Initialization of Long Short-Term Memory Networks
Weight initialization is important for faster convergence and stability ...
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Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning
Supervised learning algorithms trained on medical images will often fail...
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Knowledge distillation for semi-supervised domain adaptation
In the absence of sufficient data variation (e.g., scanner and protocol ...
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Robust parametric modeling of Alzheimer's disease progression
Quantitative characterization of disease progression using longitudinal ...
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Training recurrent neural networks robust to incomplete data: application to Alzheimer's disease progression modeling
Disease progression modeling (DPM) using longitudinal data is a challeng...
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PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation
For proper generalization performance of convolutional neural networks (...
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On Variational Methods for Motion Compensated Inpainting
We develop in this paper a generic Bayesian framework for the joint esti...
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Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 MRIs
Segmenting vascular pathologies such as white matter lesions in Brain ma...
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Robust training of recurrent neural networks to handle missing data for disease progression modeling
Disease progression modeling (DPM) using longitudinal data is a challeng...
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Convolutional neural networks for segmentation and object detection of human semen
We compare a set of convolutional neural network (CNN) architectures for...
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Towards a theory of statistical tree-shape analysis
In order to develop statistical methods for shapes with a tree-structure...
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Higher-Order Momentum Distributions and Locally Affine LDDMM Registration
To achieve sparse parametrizations that allows intuitive analysis, we ai...
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