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Information Bottleneck: Exact Analysis of (Quantized) Neural Networks


Jun 24, 2021
Stephan Sloth Lorenzen, Christian Igel, Mads Nielsen


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CARRNN: A Continuous Autoregressive Recurrent Neural Network for Deep Representation Learning from Sporadic Temporal Data


Apr 08, 2021
Mostafa Mehdipour Ghazi, Lauge Sørensen, Sébastien Ourselin, Mads Nielsen


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Multimodal Variational Autoencoders for Semi-Supervised Learning: In Defense of Product-of-Experts


Jan 18, 2021
Svetlana Kutuzova, Oswin Krause, Douglas McCloskey, Mads Nielsen, Christian Igel


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Lung Segmentation from Chest X-rays using Variational Data Imputation


May 20, 2020
Raghavendra Selvan, Erik B. Dam, Sofus Rischel, Kaining Sheng, Mads Nielsen, Akshay Pai

* Source code, training data and the trained models are available here: https://github.com/raghavian/lungVAE/ 

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On the Initialization of Long Short-Term Memory Networks


Dec 22, 2019
Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, Marc Modat, M. Jorge Cardoso, Sebastien Ourselin, Lauge Sorensen


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Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning


Sep 17, 2019
Mauricio Orbes-Arteaga, Thomas Varsavsky, Carole H. Sudre, Zach Eaton-Rosen, Lewis J. Haddow, Lauge Sørensen, Mads Nielsen, Akshay Pai, Sébastien Ourselin, Marc Modat, Parashkev Nachev, M. Jorge Cardoso

* Accepted at 1st International Workshop on Domain Adaptation and Representation Transfer held at MICCAI 2019 

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Knowledge distillation for semi-supervised domain adaptation


Aug 16, 2019
Mauricio Orbes-Arteaga, Jorge Cardoso, Lauge Sørensen, Christian Igel, Sebastien Ourselin, Marc Modat, Mads Nielsen, Akshay Pai

* MLCN MICCAI workshop 

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Robust parametric modeling of Alzheimer's disease progression


Aug 14, 2019
Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, Marc Modat, M. Jorge Cardoso, Sébastien Ourselin, Lauge Sørensen


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Training recurrent neural networks robust to incomplete data: application to Alzheimer's disease progression modeling


Mar 17, 2019
Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, M. Jorge Cardoso, Marc Modat, Sebastien Ourselin, Lauge Sørensen

* Medical Image Analysis, Volume 53, Pages 39-46, 2019 
* arXiv admin note: substantial text overlap with arXiv:1808.05500 

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PADDIT: Probabilistic Augmentation of Data using Diffeomorphic Image Transformation


Oct 03, 2018
Mauricio Orbes Arteaga, Lauge Sørensen, Jorge Cardoso, Marc Modat, Sebastien Ourselin, Stefan Sommer, Mads Nielsen, Christian Igel, Akshay Pai


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On Variational Methods for Motion Compensated Inpainting


Sep 21, 2018
Francois Lauze, Mads Nielsen

* DIKU Technical report 2009 with some small corrections 

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Simultaneous synthesis of FLAIR and segmentation of white matter hypointensities from T1 MRIs


Aug 20, 2018
Mauricio Orbes-Arteaga, M. Jorge Cardoso, Lauge Sørensen, Marc Modat, Sébastien Ourselin, Mads Nielsen, Akshay Pai

* Conference on Medical Imaging with Deep Learning MIDL 2018 

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Robust training of recurrent neural networks to handle missing data for disease progression modeling


Aug 16, 2018
Mostafa Mehdipour Ghazi, Mads Nielsen, Akshay Pai, M. Jorge Cardoso, Marc Modat, Sebastien Ourselin, Lauge Sørensen

* 9 pages, 1 figure, MIDL conference 

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A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images


May 01, 2017
Akshay Pai, Stefan Sommer, Lars Lau Raket, Line Kühnel, Sune Darkner, Lauge Sørensen, Mads Nielsen


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Convolutional neural networks for segmentation and object detection of human semen


Apr 03, 2017
Malte Stær Nissen, Oswin Krause, Kristian Almstrup, Søren Kjærulff, Torben Trindkær Nielsen, Mads Nielsen

* Submitted for Scandinavian Conference on Image Analysis 2017 

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Higher-Order Momentum Distributions and Locally Affine LDDMM Registration


Nov 29, 2012
Stefan Sommer, Mads Nielsen, Sune Darkner, Xavier Pennec


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Towards a theory of statistical tree-shape analysis


Jul 23, 2012
Aasa Feragen, Pechin Lo, Marleen de Bruijne, Mads Nielsen, Francois Lauze

* 36 pages, 15 figures 

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