Jeffrey De Fauw

According to our database, Jeffrey De Fauw authored at least 8 papers between 2016 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

Self-Supervised MultiModal Versatile Networks.

Jean-Baptiste Alayrac, Adrià Recasens, Rosalia Schneider, Relja Arandjelovic, Jason Ramapuram, Jeffrey De Fauw, Lucas Smaira, Sander Dieleman, Andrew Zisserman

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Data-Efficient Image Recognition with Contrastive Predictive Coding.

Olivier J. Hénaff, Aravind Srinivas, Jeffrey De Fauw, Ali Razavi, Carl Doersch, S. M. Ali Eslami, Aäron van den Oord

CoRR, 2019

Hierarchical Autoregressive Image Models with Auxiliary Decoders.

Jeffrey De Fauw, Sander Dieleman, Karen Simonyan

CoRR, 2019

2018

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

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

CoRR, 2018

A Probabilistic U-Net for Segmentation of Ambiguous Images.

Simon 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

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2016

Automated analysis of retinal imaging using machine learning techniques for computer vision.

Jeffrey De Fauw, Pearse A. Keane, Nenad Tomasev, Daniel Visentin, George van den Driessche, Mike Johnson, Cían Hughes, Carlton Chu, Joseph R. Ledsam, Trevor Back, Tunde Peto, Geraint Rees, Hugh Montgomery, Rosalind Raine, Olaf Ronneberger, Julien Cornebise

F1000Research, 2016

Applying machine learning to automated segmentation of head and neck tumour volumes and organs at risk on radiotherapy planning CT and MRI scans.

Carlton Chu, Jeffrey De Fauw, Nenad Tomasev, Bernardino Romera-Paredes, Cían Hughes, Joseph R. Ledsam, Trevor Back, Hugh Montgomery, Geraint Rees, Rosalind Raine, Kevin Sullivan, Syed Ali Moinuddin, Derek D'Souza, Olaf Ronneberger, Ruheena Mendes, Julien Cornebise

F1000Research, 2016

Exploiting Cyclic Symmetry in Convolutional Neural Networks.

Sander Dieleman, Jeffrey De Fauw, Koray Kavukcuoglu

Proceedings of the 33nd International Conference on Machine Learning, 2016