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12/24/2022
GraphCast: Learning skillful medium-range global weather forecasting
We introduce a machine-learning (ML)-based weather simulator–called "Gra...
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06/07/2021
Proxy-Normalizing Activations to Match Batch Normalization while Removing Batch Dependence
We investigate the reasons for the performance degradation incurred with...
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06/07/2021
Making EfficientNet More Efficient: Exploring Batch-Independent Normalization, Group Convolutions and Reduced Resolution Training
Much recent research has been dedicated to improving the efficiency of t...
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11/09/2020
Improving Neural Network Training in Low Dimensional Random Bases
Stochastic Gradient Descent (SGD) has proven to be remarkably effective ...
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08/16/2019
Multi-Domain Adaptation in Brain MRI through Paired Consistency and Adversarial Learning
Supervised learning algorithms trained on medical images will often fail...
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07/25/2019
As easy as 1, 2... 4? Uncertainty in counting tasks for medical imaging
Counting is a fundamental task in biomedical imaging and count is an imp...
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07/17/2018
PIMMS: Permutation Invariant Multi-Modal Segmentation
In a research context, image acquisition will often involve a pre-define...
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06/22/2018
Towards safe deep learning: accurately quantifying biomarker uncertainty in neural network predictions
Automated medical image segmentation, specifically using deep learning, ...
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06/18/2018
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning
Multi-task neural network architectures provide a mechanism that jointly...
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09/11/2017