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2020 – today
- 2023
[i19]Shruthi Bannur, Stephanie L. Hyland, Qianchu Liu, Fernando Pérez-García
, Maximilian Ilse, Daniel C. Castro, Benedikt Boecking, Harshita Sharma, Kenza Bouzid, Anja Thieme, Anton Schwaighofer, Maria Wetscherek, Matthew P. Lungren, Aditya V. Nori, Javier Alvarez-Valle, Ozan Oktay:
Learning to Exploit Temporal Structure for Biomedical Vision-Language Processing. CoRR abs/2301.04558 (2023)- [i18]Miguel Monteiro, Fabio De Sousa Ribeiro, Nick Pawlowski, Daniel C. Castro, Ben Glocker:
Measuring axiomatic soundness of counterfactual image models. CoRR abs/2303.01274 (2023) - 2022
- [c13]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. ECCV (36) 2022: 1-21 - [c12]Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker:
Deep Structural Causal Shape Models. ECCV Workshops (6) 2022: 400-432 - [c11]Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker:
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation. ML4H@NeurIPS 2022: 290-310 - [i17]Benedikt Boecking, Naoto Usuyama, Shruthi Bannur, Daniel C. Castro, Anton Schwaighofer, Stephanie L. Hyland, Maria Wetscherek, Tristan Naumann, Aditya V. Nori, Javier Alvarez-Valle, Hoifung Poon, Ozan Oktay:
Making the Most of Text Semantics to Improve Biomedical Vision-Language Processing. CoRR abs/2204.09817 (2022) - [i16]Rajat Rasal, Daniel C. Castro, Nick Pawlowski, Ben Glocker:
Deep Structural Causal Shape Models. CoRR abs/2208.10950 (2022) - [i15]Margherita Rosnati, Fabio De Sousa Ribeiro, Miguel Monteiro, Daniel Coelho de Castro, Ben Glocker:
Analysing the effectiveness of a generative model for semi-supervised medical image segmentation. CoRR abs/2211.01886 (2022) - 2021
- [i14]Shruthi Bannur, Ozan Oktay, Melanie Bernhardt, Anton Schwaighofer, Rajesh Jena, Besmira Nushi, Sharan Wadhwani, Aditya V. Nori, Kal Natarajan, Shazad Ashraf, Javier Alvarez-Valle, Daniel C. Castro:
Hierarchical Analysis of Visual COVID-19 Features from Chest Radiographs. CoRR abs/2107.06618 (2021) - [i13]Melanie Bernhardt, Daniel C. Castro, Ryutaro Tanno, Anton Schwaighofer, Kerem Can Tezcan, Miguel Monteiro, Shruthi Bannur, Matthew P. Lungren, Aditya V. Nori, Ben Glocker, Javier Alvarez-Valle, Ozan Oktay:
Active label cleaning: Improving dataset quality under resource constraints. CoRR abs/2109.00574 (2021) - 2020
- [c10]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Ben Glocker:
Image-Level Harmonization of Multi-site Data Using Image-and-Spatial Transformer Networks. MICCAI (7) 2020: 710-719 - [c9]Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker:
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. NeurIPS 2020 - [c8]Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker:
Deep Structural Causal Models for Tractable Counterfactual Inference. NeurIPS 2020 - [i12]Miguel Monteiro, Loïc Le Folgoc, Daniel Coelho de Castro, Nick Pawlowski, Bernardo Marques, Konstantinos Kamnitsas, Mark van der Wilk, Ben Glocker:
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty. CoRR abs/2006.06015 (2020) - [i11]Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker:
Deep Structural Causal Models for Tractable Counterfactual Inference. CoRR abs/2006.06485 (2020) - [i10]Robert Robinson, Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Marius de Groot, Ronald M. Summers, Daniel Rueckert, Benjamin M. Glocker:
Image-level Harmonization of Multi-Site Data using Image-and-Spatial Transformer Networks. CoRR abs/2006.16741 (2020)
2010 – 2019
- 2019
- [j1]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. J. Mach. Learn. Res. 20: 178:1-178:29 (2019) - [c7]Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker:
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. IPMI 2019: 221-234 - [c6]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. NeurIPS 2019: 6447-6458 - [i9]Loïc Le Folgoc, Daniel Coelho de Castro, Jeremy Tan, Bishesh Khanal, Konstantinos Kamnitsas, Ian Walker, Amir Alansary, Ben Glocker:
Controlling Meshes via Curvature: Spin Transformations for Pose-Invariant Shape Processing. CoRR abs/1903.02429 (2019) - [i8]Ben Glocker, Robert Robinson, Daniel Coelho de Castro, Qi Dou, Ender Konukoglu:
Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effects. CoRR abs/1910.04597 (2019) - [i7]Qi Dou, Daniel Coelho de Castro, Konstantinos Kamnitsas, Ben Glocker:
Domain Generalization via Model-Agnostic Learning of Semantic Features. CoRR abs/1910.13580 (2019) - [i6]Daniel Coelho de Castro, Ian Walker, Ben Glocker:
Causality matters in medical imaging. CoRR abs/1912.08142 (2019) - 2018
- [c5]Daniel Coelho de Castro, Sebastian Nowozin:
From Face Recognition to Models of Identity: A Bayesian Approach to Learning About Unknown Identities from Unsupervised Data. ECCV (2) 2018: 764-780 - [c4]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. ICML 2018: 2464-2473 - [c3]Jo Schlemper, Daniel Coelho de Castro, Wenjia Bai, Chen Qin, Ozan Oktay, Jinming Duan, Anthony N. Price, Joseph V. Hajnal, Daniel Rueckert:
Bayesian Deep Learning for Accelerated MR Image Reconstruction. MLMIR@MICCAI 2018: 64-71 - [c2]Daniel Coelho de Castro, Ben Glocker:
Nonparametric Density Flows for MRI Intensity Normalisation. MICCAI (1) 2018: 206-214 - [c1]Jo Schlemper, Ozan Oktay, Wenjia Bai, Daniel Coelho de Castro, Jinming Duan, Chen Qin, Joseph V. Hajnal, Daniel Rueckert:
Cardiac MR Segmentation from Undersampled k-space Using Deep Latent Representation Learning. MICCAI (1) 2018: 259-267 - [i5]Daniel Coelho de Castro, Ben Glocker:
Nonparametric Density Flows for MRI Intensity Normalisation. CoRR abs/1806.02613 (2018) - [i4]Konstantinos Kamnitsas, Daniel Coelho de Castro, Loïc Le Folgoc, Ian Walker, Ryutaro Tanno, Daniel Rueckert, Ben Glocker, Antonio Criminisi, Aditya V. Nori:
Semi-Supervised Learning via Compact Latent Space Clustering. CoRR abs/1806.02679 (2018) - [i3]Daniel Coelho de Castro, Sebastian Nowozin:
From Face Recognition to Models of Identity: A Bayesian Approach to Learning about Unknown Identities from Unsupervised Data. CoRR abs/1807.07872 (2018) - [i2]Daniel Coelho de Castro, Jeremy Tan, Bernhard Kainz, Ender Konukoglu, Ben Glocker:
Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning. CoRR abs/1809.10780 (2018) - [i1]Daniel Coelho de Castro, Sebastian Nowozin:
Contextual Face Recognition with a Nested-Hierarchical Nonparametric Identity Model. CoRR abs/1811.07753 (2018)
Coauthor Index
aka: Benjamin M. Glocker
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