Andrew Jesson
Andrew Jesson
Verified email at cs.ox.ac.uk
Title
Cited by
Cited by
Year
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
6782018
Longitudinal multiple sclerosis lesion segmentation: resource and challenge
A Carass, S Roy, A Jog, JL Cuzzocreo, E Magrath, A Gherman, J Button, ...
NeuroImage 148, 77-102, 2017
1742017
Cased: Curriculum adaptive sampling for extreme data imbalance
A Jesson, N Guizard, SH Ghalehjegh, D Goblot, F Soudan, N Chapados
International Conference on Medical Image Computing and Computer-Assisted …, 2017
352017
Brain tumor segmentation using a 3d fcn with multi-scale loss
A Jesson, T Arbel
International MICCAI Brainlesion Workshop, 392-402, 2017
342017
Hierarchical MRF and random forest segmentation of MS lesions and healthy tissues in brain MRI
A Jesson, T Arbel
proceedings of the 2015 longitudinal multiple sclerosis lesion segmentation …, 2015
332015
Evaluating white matter lesion segmentations with refined Sørensen-Dice analysis
A Carass, S Roy, A Gherman, JC Reinhold, A Jesson, T Arbel, O Maier, ...
Scientific reports 10 (1), 1-19, 2020
242020
Attentive task-agnostic meta-learning for few-shot text classification
X Jiang, M Havaei, G Chartrand, H Chouaib, T Vincent, A Jesson, ...
20*2018
Identifying causal-effect inference failure with uncertainty-aware models
A Jesson, S Mindermann, U Shalit, Y Gal
Advances in Neural Information Processing Systems 33, 2020
172020
On feature collapse and deep kernel learning for single forward pass uncertainty
J van Amersfoort, L Smith, A Jesson, O Key, Y Gal
arXiv preprint arXiv:2102.11409, 2021
10*2021
Task adaptive metric space for medium-shot medical image classification
X Jiang, L Ding, M Havaei, A Jesson, S Matwin
International Conference on Medical Image Computing and Computer-Assisted …, 2019
102019
Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding
A Jesson, S Mindermann, Y Gal, U Shalit
ICML, 2021
22021
Adversarially learned mixture model
A Jesson, C Low-Kam, F Soudan, N Chapados
ICML Workshop: Theoretical Foundations and Applications of Deep Generative …, 2018
12018
Method and system for generating synthetically anonymized data for a given task
F Chandelier, A Jesson, M Havaei, L Dijorio, LOWKAM Cevile, ...
US Patent App. 17/259,908, 2021
2021
Brain Lesion Detection and Tumor Segmentation in MRI Using 3D Fully Convolutional Networks
A Jesson
PQDT-Global, 2019
2019
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Articles 1–14