Measurement of Myelin in the Preterm Brain: Multi-compartment Diffusion Imaging and Multi-component T2 Relaxometry. - Andrew Melbourne; Zach Eaton-Rosen; Alan Bainbridge; Giles S. Kendall; Manuel Jorge Cardoso; Nicola J. Robertson; Neil Marlow; Sébastien Ourselin (MICCAI (2), 2013)

Longitudinal Measurement of the Developing Thalamus in the Preterm Brain Using Multi-modal MRI. - Zach Eaton-Rosen; Andrew Melbourne; Eliza Orasanu; Marc Modat; Manuel Jorge Cardoso; Alan Bainbridge; Giles S. Kendall; Nicola J. Robertson; Neil Marlow; Sébastien Ourselin (MICCAI (2), 2014)

Multi-modal Measurement of the Myelin-to-Axon Diameter g-ratio in Preterm-born Neonates and Adult Controls. - 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 (MICCAI (2), 2014)

Measuring Cortical Neurite-Dispersion and Perfusion in Preterm-Born Adolescents Using Multi-modal MRI. - Andrew Melbourne; Zach Eaton-Rosen; David Owen 001; M. Jorge Cardoso; Joanne Beckmann; David Atkinson; Neil Marlow; Sébastien Ourselin (MICCAI (3), 2015)

Longitudinal measurement of the developing grey matter in preterm subjects using multi-modal MRI. - Zach Eaton-Rosen; Andrew Melbourne; Eliza Orasanu; Manuel Jorge Cardoso; Marc Modat; Alan Bainbridge; Giles S. Kendall; Nicola J. Robertson; Neil Marlow; Sébastien Ourselin (NeuroImage, 2015)

Beyond the Resolution Limit: Diffusion Parameter Estimation in Partial Volume. - Zach Eaton-Rosen; Andrew Melbourne; M. Jorge Cardoso; Neil Marlow; Sébastien Ourselin (MICCAI (3), 2016)

Fitting parametric models of diffusion MRI in regions of partial volume. - Zach Eaton-Rosen; Manuel Jorge Cardoso; Andrew Melbourne; Eliza Orasanu; Alan Bainbridge; Giles S. Kendall; Nicola J. Robertson; Neil Marlow; Sébastien Ourselin (Image Processing, 2016)

Anatomy-Driven Modelling of Spatial Correlation for Regularisation of Arterial Spin Labelling Images. - David Owen 001; Andrew Melbourne; Zach Eaton-Rosen; David Thomas 002; Neil Marlow; Jonathan D. Rohrer; Sébastien Ourselin (MICCAI (2), 2017)

NiftyNet: a deep-learning platform for medical imaging. - Eli Gibson; Wenqi Li 001; Carole H. Sudre; Lucas Fidon; Dzhoshkun I. Shakir; Guotai Wang; Zach Eaton-Rosen; Robert J. Gray; Tom Doel; Yipeng Hu; Tom Whyntie; Parashkev Nachev; et al. (CoRR, 2017)

Investigating the maturation of microstructure and radial orientation in the preterm human cortex with diffusion MRI. - Zach Eaton-Rosen; Benoît Scherrer; Andrew Melbourne; Sébastien Ourselin; Jeffrey J. Neil; Simon K. Warfield (NeuroImage, 2017)

Deep Convolutional Filtering for Spatio-Temporal Denoising and Artifact Removal in Arterial Spin Labelling MRI. - David Owen 001; Andrew Melbourne; Zach Eaton-Rosen; David L. Thomas; Neil Marlow; Jonathan D. Rohrer; Sébastien Ourselin (MICCAI (1), 2018)

Uncertainty in Multitask Learning: Joint Representations for Probabilistic MR-only Radiotherapy Planning. - Felix J. S. Bragman; Ryutaro Tanno; Zach Eaton-Rosen; Wenqi Li 001; David J. Hawkes; Sébastien Ourselin; Daniel C. Alexander; Jamie R. McClelland; M. Jorge Cardoso (MICCAI (4), 2018)

Towards Safe Deep Learning: Accurately Quantifying Biomarker Uncertainty in Neural Network Predictions. - Zach Eaton-Rosen; Felix J. S. Bragman; Sotirios Bisdas; Sébastien Ourselin; M. Jorge Cardoso (MICCAI (1), 2018)

PIMMS: Permutation Invariant Multi-modal Segmentation. - Thomas Varsavsky; Zach Eaton-Rosen; Carole H. Sudre; Parashkev Nachev; M. Jorge Cardoso (DLMIA/ML-CDS@MICCAI, 2018)

NiftyNet: a deep-learning platform for medical imaging. - Eli Gibson; Wenqi Li 001; Carole H. Sudre; Lucas Fidon; Dzhoshkun I. Shakir; Guotai Wang; Zach Eaton-Rosen; Robert J. Gray; Tom Doel; Yipeng Hu; Tom Whyntie; Parashkev Nachev; et al. (Comput. Methods Programs Biomed., 2018)

As Easy as 1, 2...4? Uncertainty in Counting Tasks for Medical Imaging. - Zach Eaton-Rosen; Thomas Varsavsky; Sébastien Ourselin; M. Jorge Cardoso (MICCAI (4), 2019)

Multi-domain Adaptation in Brain MRI Through Paired Consistency and Adversarial Learning. - 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 (DART/MIL3ID@MICCAI, 2019)

Improving Neural Network Training in Low Dimensional Random Bases. - Frithjof Gressmann; Zach Eaton-Rosen; Carlo Luschi (NeurIPS, 2020)

Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence. - Antoine Labatie; Dominic Masters; Zach Eaton-Rosen; Carlo Luschi (NeurIPS, 2021)

Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training. - Dominic Masters; Antoine Labatie; Zach Eaton-Rosen; Carlo Luschi (CoRR, 2021)

GraphCast: Learning skillful medium-range global weather forecasting. - 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; et al. (CoRR, 2022)

Imagen 3. - 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; et al. (CoRR, 2024)