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05/30/2019
A Hierarchical Probabilistic U-Net for Modeling Multi-Scale Ambiguities
Medical imaging only indirectly measures the molecular identity of the t...
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09/12/2018
Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy
Over half a million individuals are diagnosed with head and neck cancer ...
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06/13/2018
A Probabilistic U-Net for Segmentation of Ambiguous Images
Many real-world vision problems suffer from inherent ambiguities. In cli...
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12/03/2015
Prototypical Priors: From Improving Classification to Zero-Shot Learning
Recent works on zero-shot learning make use of side information such as ...
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11/25/2015
Recurrent Instance Segmentation
Instance segmentation is the problem of detecting and delineating each d...
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05/23/2015
The Benefit of Multitask Representation Learning
We discuss a general method to learn data representations from multiple ...
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02/11/2015
Conditional Random Fields as Recurrent Neural Networks
Pixel-level labelling tasks, such as semantic segmentation, play a centr...
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02/08/2014
An Inequality with Applications to Structured Sparsity and Multitask Dictionary Learning
From concentration inequalities for the suprema of Gaussian or Rademache...
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07/17/2013
A New Convex Relaxation for Tensor Completion
We study the problem of learning a tensor from a set of linear measureme...
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09/04/2012