1 code implementation • ICLR 2022 • Johannes Brandstetter, Daniel Worrall, Max Welling
The numerical solution of partial differential equations (PDEs) is difficult, having led to a century of research so far.
1 code implementation • 29 Nov 2019 • Christina Winkler, Daniel Worrall, Emiel Hoogeboom, Max Welling
Normalizing Flows (NFs) are able to model complicated distributions p(y) with strong inter-dimensional correlations and high multimodality by transforming a simple base density p(z) through an invertible neural network under the change of variables formula.
no code implementations • 31 Jul 2019 • Ryutaro Tanno, Daniel Worrall, Enrico Kaden, Aurobrata Ghosh, Francesco Grussu, Alberto Bizzi, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander
Here we introduce methods to characterise different components of uncertainty in such problems and demonstrate the ideas using diffusion MRI super-resolution.
1 code implementation • 3 Jul 2019 • Shi Hu, Daniel Worrall, Stefan Knegt, Bas Veeling, Henkjan Huisman, Max Welling
The accurate estimation of predictive uncertainty carries importance in medical scenarios such as lung node segmentation.
no code implementations • ECCV 2018 • Daniel Worrall, Gabriel Brostow
3D Convolutional Neural Networks are sensitive to transformations applied to their input.