Get our free extension to see links to code for papers anywhere online!

Chrome logo Add to Chrome

Firefox logo Add to Firefox
Picture for Bernardino Romera-Paredes

Bernardino Romera-Paredes

A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities


May 30, 2019
Simon A. A. Kohl, Bernardino Romera-Paredes, Klaus H. Maier-Hein, Danilo Jimenez Rezende, S. M. Ali Eslami, Pushmeet Kohli, Andrew Zisserman, Olaf Ronneberger

Figure 1 for A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
Figure 2 for A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
Figure 3 for A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
Figure 4 for A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
* 25 pages, 15 figures 
  Access Paper or Ask Questions

A Probabilistic U-Net for Segmentation of Ambiguous Images


Oct 29, 2018
Simon A. A. Kohl, Bernardino Romera-Paredes, Clemens Meyer, Jeffrey De Fauw, Joseph R. Ledsam, Klaus H. Maier-Hein, S. M. Ali Eslami, Danilo Jimenez Rezende, Olaf Ronneberger

Figure 1 for A Probabilistic U-Net for Segmentation of Ambiguous Images
Figure 2 for A Probabilistic U-Net for Segmentation of Ambiguous Images
Figure 3 for A Probabilistic U-Net for Segmentation of Ambiguous Images
Figure 4 for A Probabilistic U-Net for Segmentation of Ambiguous Images
* 11 pages for the main paper, 28 pages including appendix. 5 figures in the main paper, 18 figures in total, Advances in Neural Information Processing Systems (NIPS), 2018 
  Access Paper or Ask Questions

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy


Sep 12, 2018
Stanislav Nikolov, Sam Blackwell, Ruheena Mendes, Jeffrey De Fauw, Clemens Meyer, Cían Hughes, Harry Askham, Bernardino Romera-Paredes, Alan Karthikesalingam, Carlton Chu, Dawn Carnell, Cheng Boon, Derek D'Souza, Syed Ali Moinuddin, Kevin Sullivan, DeepMind Radiographer Consortium, Hugh Montgomery, Geraint Rees, Ricky Sharma, Mustafa Suleyman, Trevor Back, Joseph R. Ledsam, Olaf Ronneberger

Figure 1 for Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Figure 2 for Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Figure 3 for Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Figure 4 for Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

  Access Paper or Ask Questions

Prototypical Priors: From Improving Classification to Zero-Shot Learning


Apr 25, 2018
Saumya Jetley, Bernardino Romera-Paredes, Sadeep Jayasumana, Philip Torr

Figure 1 for Prototypical Priors: From Improving Classification to Zero-Shot Learning
Figure 2 for Prototypical Priors: From Improving Classification to Zero-Shot Learning
Figure 3 for Prototypical Priors: From Improving Classification to Zero-Shot Learning
Figure 4 for Prototypical Priors: From Improving Classification to Zero-Shot Learning
* 12 Pages, 6 Figures, 2 Tables, in British Machine Vision Conference (BMVC), 2015 
  Access Paper or Ask Questions

Recurrent Instance Segmentation


Oct 24, 2016
Bernardino Romera-Paredes, Philip H. S. Torr

Figure 1 for Recurrent Instance Segmentation
Figure 2 for Recurrent Instance Segmentation
Figure 3 for Recurrent Instance Segmentation
Figure 4 for Recurrent Instance Segmentation
* ECCV 2016. 14th European Conference on Computer Vision 
 * 14 pages (main paper). 24 pages including references and appendix 
  Access Paper or Ask Questions

Conditional Random Fields as Recurrent Neural Networks


Apr 13, 2016
Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr

Figure 1 for Conditional Random Fields as Recurrent Neural Networks
Figure 2 for Conditional Random Fields as Recurrent Neural Networks
Figure 3 for Conditional Random Fields as Recurrent Neural Networks
Figure 4 for Conditional Random Fields as Recurrent Neural Networks
* This paper is published in IEEE ICCV 2015 
  Access Paper or Ask Questions

The Benefit of Multitask Representation Learning


Mar 25, 2016
Andreas Maurer, Massimiliano Pontil, Bernardino Romera-Paredes

Figure 1 for The Benefit of Multitask Representation Learning
Figure 2 for The Benefit of Multitask Representation Learning
Figure 3 for The Benefit of Multitask Representation Learning
Figure 4 for The Benefit of Multitask Representation Learning
* To appear in Journal of Machine Learning Research (JMLR). 31 pages 
  Access Paper or Ask Questions

Sparse coding for multitask and transfer learning


Jun 16, 2014
Andreas Maurer, Massimiliano Pontil, Bernardino Romera-Paredes

Figure 1 for Sparse coding for multitask and transfer learning
Figure 2 for Sparse coding for multitask and transfer learning
Figure 3 for Sparse coding for multitask and transfer learning
Figure 4 for Sparse coding for multitask and transfer learning
* International Conference on Machine Learning 2013 
  Access Paper or Ask Questions

An Inequality with Applications to Structured Sparsity and Multitask Dictionary Learning


Jun 07, 2014
Andreas Maurer, Massimiliano Pontil, Bernardino Romera-Paredes


  Access Paper or Ask Questions

A New Convex Relaxation for Tensor Completion


Jul 17, 2013
Bernardino Romera-Paredes, Massimiliano Pontil

Figure 1 for A New Convex Relaxation for Tensor Completion
Figure 2 for A New Convex Relaxation for Tensor Completion

  Access Paper or Ask Questions