Articles with public access mandates - Andrew JessonLearn more
Not available anywhere: 1
Brain tumor segmentation using a 3D FCN with multi-scale loss
A Jesson, T Arbel
International MICCAI Brainlesion Workshop, 392-402, 2017
Mandates: Natural Sciences and Engineering Research Council of Canada
Available somewhere: 10
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
Mandates: US National Institutes of Health, UK Engineering and Physical Sciences …
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), 8242, 2020
Mandates: US National Institutes of Health
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
Mandates: UK Engineering and Physical Sciences Research Council
Interventions, where and how? experimental design for causal models at scale
P Tigas*, Y Annadani*, A Jesson, B Schölkopf, Y Gal, S Bauer
Advances in Neural Information Processing Systems (NeurIPS) 36, 2022
Mandates: UK Engineering and Physical Sciences Research Council
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data
A Jesson*, P Tigas*, J van Amersfoort, A Kirsch, U Shalit, Y Gal
Advances in Neural Information Processing Systems (NeurIPS) 35, 2021
Mandates: UK Engineering and Physical Sciences Research Council
Scalable Sensitivity and Uncertainty Analysis for Causal-Effect Estimates of Continuous-Valued Interventions
A Jesson, A Douglas, P Manshausen, N Meinshausen, P Stier, Y Gal, ...
Advances in Neural Information Processing Systems (NeurIPS) 36, 2022
Mandates: European Commission
B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding
M Oprescu, J Dorn, M Ghoummaid, A Jesson, N Kallus, U Shalit
40th International Conference on Machine Learning (ICML), 2023
Mandates: US National Science Foundation, US Department of Energy
Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacific
A Jesson*, P Manshausen*, A Douglas*, D Watson-Parris, Y Gal, P Stier
Causal Inference & Machine Learning: Why now? (NeurIPS Wokshop), 2021
Mandates: European Commission
Partial identification of dose responses with hidden confounders
MG Marmarelis, E Haddad, A Jesson, N Jahanshad, A Galstyan, ...
Uncertainty in Artificial Intelligence, 1368-1379, 2023
Mandates: US Department of Defense
DiscoBAX-Discovery of optimal intervention sets in genomic experiment design
C Lyle, A Mehrjou, P Notin, A Jesson, S Bauer, Y Gal, P Schwab
40th International Conference on Machine Learning (ICML), 2023
Mandates: UK Engineering and Physical Sciences Research Council
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