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Journal Articles
- 2018
[j3]Eli Gibson
, Wenqi Li, Carole H. Sudre, Lucas Fidon, Dzhoshkun I. Shakir, Guotai Wang, Zach Eaton-Rosen, Robert J. Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Marc Modat, Dean C. Barratt, Sébastien Ourselin, M. Jorge Cardoso, Tom Vercauteren:
NiftyNet: a deep-learning platform for medical imaging. Comput. Methods Programs Biomed. 158: 113-122 (2018)- 2017
- [j2]Zach Eaton-Rosen, Benoît Scherrer, Andrew Melbourne, Sébastien Ourselin, Jeffrey J. Neil, Simon K. Warfield:
Investigating the maturation of microstructure and radial orientation in the preterm human cortex with diffusion MRI. NeuroImage 162: 65-72 (2017) - 2015
- [j1]Zach Eaton-Rosen, Andrew Melbourne, Eliza Orasanu, Manuel Jorge Cardoso, Marc Modat, Alan Bainbridge, Giles S. Kendall, Nicola J. Robertson, Neil Marlow, Sébastien Ourselin:
Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI. NeuroImage 111: 580-589 (2015)
Conference and Workshop Papers
- 2021
- [c15]Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi:
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. NeurIPS 2021: 16990-17006 - 2020
- [c14]Frithjof Gressmann, Zach Eaton-Rosen, Carlo Luschi:
Improving Neural Network Training in Low Dimensional Random Bases. NeurIPS 2020 - 2019
- [c13]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:
Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning. DART/MIL3ID@MICCAI 2019: 54-62 - [c12]Zach Eaton-Rosen, Thomas Varsavsky, Sébastien Ourselin, M. Jorge Cardoso:
As Easy as 1, 2...4? Uncertainty in Counting Tasks for Medical Imaging. MICCAI (4) 2019: 356-364 - 2018
- [c11]Felix J. S. Bragman, Ryutaro Tanno, Zach Eaton-Rosen, Wenqi Li, David J. Hawkes, Sébastien Ourselin, Daniel C. Alexander, Jamie R. McClelland, M. Jorge Cardoso:
Uncertainty in Multitask Learning: Joint Representations for Probabilistic MR-only Radiotherapy Planning. MICCAI (4) 2018: 3-11 - [c10]David Owen, Andrew Melbourne, Zach Eaton-Rosen, David L. Thomas, Neil Marlow, Jonathan D. Rohrer, Sébastien Ourselin:
Deep Convolutional Filtering for Spatio-Temporal Denoising and Artifact Removal in Arterial Spin Labelling MRI. MICCAI (1) 2018: 21-29 - [c9]Thomas Varsavsky, Zach Eaton-Rosen, Carole H. Sudre, Parashkev Nachev, M. Jorge Cardoso:
PIMMS: Permutation Invariant Multi-modal Segmentation. DLMIA/ML-CDS@MICCAI 2018: 201-209 - [c8]Zach Eaton-Rosen, Felix J. S. Bragman, Sotirios Bisdas, Sébastien Ourselin, M. Jorge Cardoso:
Towards Safe Deep Learning: Accurately Quantifying Biomarker Uncertainty in Neural Network Predictions. MICCAI (1) 2018: 691-699 - 2017
- [c7]David Owen, Andrew Melbourne, Zach Eaton-Rosen, David Thomas, Neil Marlow, Jonathan D. Rohrer, Sébastien Ourselin:
Anatomy-Driven Modelling of Spatial Correlation for Regularisation of Arterial Spin Labelling Images. MICCAI (2) 2017: 190-197 - 2016
- [c6]Zach Eaton-Rosen, Andrew Melbourne, M. Jorge Cardoso, Neil Marlow, Sébastien Ourselin:
Beyond the Resolution Limit: Diffusion Parameter Estimation in Partial Volume. MICCAI (3) 2016: 605-612 - [c5]Zach Eaton-Rosen, Manuel Jorge Cardoso, Andrew Melbourne, Eliza Orasanu, Alan Bainbridge, Giles S. Kendall, Nicola J. Robertson, Neil Marlow, Sébastien Ourselin:
Fitting parametric models of diffusion MRI in regions of partial volume. Medical Imaging: Image Processing 2016: 97843E - 2015
- [c4]Andrew Melbourne, Zach Eaton-Rosen, David Owen, M. Jorge Cardoso, Joanne Beckmann, David Atkinson, Neil Marlow, Sébastien Ourselin:
Measuring Cortical Neurite-Dispersion and Perfusion in Preterm-Born Adolescents Using Multi-modal MRI. MICCAI (3) 2015: 72-79 - 2014
- [c3]Andrew Melbourne, Zach Eaton-Rosen, Enrico De Vita, Alan Bainbridge, Manuel Jorge Cardoso, David Price, Ernest Cady, Giles S. Kendall, Nicola J. Robertson, Neil Marlow, Sébastien Ourselin:
Multi-modal Measurement of the Myelin-to-Axon Diameter g-ratio in Preterm-born Neonates and Adult Controls. MICCAI (2) 2014: 268-275 - [c2]Zach Eaton-Rosen, Andrew Melbourne, Eliza Orasanu, Marc Modat, Manuel Jorge Cardoso, Alan Bainbridge, Giles S. Kendall, Nicola J. Robertson, Neil Marlow, Sébastien Ourselin:
Longitudinal Measurement of the Developing Thalamus in the Preterm Brain Using Multi-modal MRI. MICCAI (2) 2014: 276-283 - 2013
- [c1]Andrew Melbourne, Zach Eaton-Rosen, Alan Bainbridge, Giles S. Kendall, Manuel Jorge Cardoso, Nicola J. Robertson, Neil Marlow, Sébastien Ourselin:
Measurement of Myelin in the Preterm Brain: Multi-compartment Diffusion Imaging and Multi-component T2 Relaxometry. MICCAI (2) 2013: 336-344
Informal and Other Publications
- 2024
- [i11]Jason Baldridge, Jakob Bauer, Mukul Bhutani, Nicole Brichtova, Andrew Bunner, Kelvin Chan, Yichang Chen, Sander Dieleman, Yuqing Du, Zach Eaton-Rosen, Hongliang Fei, Nando de Freitas, Yilin Gao, Evgeny Gladchenko, Sergio Gómez Colmenarejo, Mandy Guo, Alex Haig, Will Hawkins, Hexiang Hu, Huilian Huang, Tobenna Peter Igwe, Christos Kaplanis, Siavash Khodadadeh, Yelin Kim, Ksenia Konyushkova, Karol Langner, Eric Lau, Shixin Luo, Sona Mokrá, Henna Nandwani, Yasumasa Onoe, Aäron van den Oord, Zarana Parekh, Jordi Pont-Tuset, Hang Qi, Rui Qian, Deepak Ramachandran, Poorva Rane, Abdullah Rashwan, Ali Razavi, Robert Riachi, Hansa Srinivasan, Srivatsan Srinivasan, Robin Strudel, Benigno Uria, Oliver Wang, Su Wang, Austin Waters, Chris Wolff, Auriel Wright, Zhisheng Xiao, Hao Xiong, Keyang Xu, Marc van Zee, Junlin Zhang, Katie Zhang, Wenlei Zhou, Konrad Zolna, Ola Aboubakar, Canfer Akbulut, Oscar Akerlund, Isabela Albuquerque, Nina Anderson, Marco Andreetto, Lora Aroyo, Ben Bariach, David Barker, Sherry Ben, Dana Berman, Courtney Biles, Irina Blok, Pankil Botadra, Jenny Brennan, Karla Brown, John Buckley, Rudy Bunel, Elie Bursztein, Christina Butterfield, Ben Caine, Viral Carpenter, Norman Casagrande, Ming-Wei Chang, Solomon Chang, Shamik Chaudhuri, Tony Chen, John Choi, Dmitry Churbanau, Nathan Clement, Matan Cohen, Forrester Cole, Mikhail Dektiarev, Vincent Du, Praneet Dutta, Tom Eccles, Ndidi Elue, Ashley Feden, Shlomi Fruchter, Frankie Garcia, Roopal Garg:
Imagen 3. CoRR abs/2408.07009 (2024) - 2022
- [i10]Rémi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson, Peter Wirnsberger, Meire Fortunato, Alexander Pritzel, Suman V. Ravuri, Timo Ewalds, Ferran Alet, Zach Eaton-Rosen, Weihua Hu, Alexander Merose, Stephan Hoyer, George Holland, Jacklynn Stott, Oriol Vinyals, Shakir Mohamed, Peter W. Battaglia:
GraphCast: Learning skillful medium-range global weather forecasting. CoRR abs/2212.12794 (2022) - 2021
- [i9]Dominic Masters, Antoine Labatie, Zach Eaton-Rosen, Carlo Luschi:
Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training. CoRR abs/2106.03640 (2021) - [i8]Antoine Labatie, Dominic Masters, Zach Eaton-Rosen, Carlo Luschi:
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. CoRR abs/2106.03743 (2021) - 2020
- [i7]Frithjof Gressmann, Zach Eaton-Rosen, Carlo Luschi:
Improving Neural Network Training in Low Dimensional Random Bases. CoRR abs/2011.04720 (2020) - 2019
- [i6]Zach Eaton-Rosen, Thomas Varsavsky, Sébastien Ourselin, M. Jorge Cardoso:
As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging. CoRR abs/1907.11555 (2019) - [i5]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, Manuel Jorge Cardoso:
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning. CoRR abs/1908.05959 (2019) - 2018
- [i4]Felix J. S. Bragman, Ryutaro Tanno, Zach Eaton-Rosen, Wenqi Li, David J. Hawkes, Sébastien Ourselin, Daniel C. Alexander, Jamie R. McClelland, M. Jorge Cardoso:
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning. CoRR abs/1806.06595 (2018) - [i3]Zach Eaton-Rosen, Felix J. S. Bragman, Sotirios Bisdas, Sébastien Ourselin, M. Jorge Cardoso:
Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions. CoRR abs/1806.08640 (2018) - [i2]Thomas Varsavsky, Zach Eaton-Rosen, Carole H. Sudre, Parashkev Nachev, M. Jorge Cardoso:
PIMMS: Permutation Invariant Multi-Modal Segmentation. CoRR abs/1807.06537 (2018) - 2017
- [i1]Eli Gibson, Wenqi Li, Carole H. Sudre, Lucas Fidon, Dzhoshkun I. Shakir, Guotai Wang, Zach Eaton-Rosen, Robert J. Gray, Tom Doel, Yipeng Hu, Tom Whyntie, Parashkev Nachev, Dean C. Barratt, Sébastien Ourselin, M. Jorge Cardoso, Tom Vercauteren:
NiftyNet: a deep-learning platform for medical imaging. CoRR abs/1709.03485 (2017)
Coauthor Index
aka: M. Jorge Cardoso
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