Daniel E. Worrall

According to our database, Daniel E. Worrall authored at least 21 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Neural Simulated Annealing.

Alvaro H. C. Correia, Daniel E. Worrall, Roberto Bondesan

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Lie Point Symmetry Data Augmentation for Neural PDE Solvers.

Johannes Brandstetter, Max Welling, Daniel E. Worrall

Proceedings of the International Conference on Machine Learning, 2022

Message Passing Neural PDE Solvers.

Johannes Brandstetter, Daniel E. Worrall, Max Welling

Proceedings of the Tenth International Conference on Learning Representations, 2022

Learning Perturbations for Soft-Output Linear MIMO Demappers.

Daniel E. Worrall, Markus Peschl, Arash Behboodi, Roberto Bondesan

Proceedings of the IEEE Global Communications Conference, 2022

2021

Uncertainty modelling in deep learning for safer neuroimage enhancement: Demonstration in diffusion MRI.

Ryutaro Tanno, Daniel E. Worrall, Enrico Kaden, Aurobrata Ghosh, Francesco Grussu, Alberto Bizzi, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander

NeuroImage, 2021

2020

MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning.

Elise van der Pol, Daniel E. Worrall, Herke van Hoof, Frans A. Oliehoek, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks.

Fabian Fuchs, Daniel E. Worrall, Volker Fischer, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Equivariance for deep learning and retinal imaging.

Daniel E. Worrall

PhD thesis, 2019

Learning Likelihoods with Conditional Normalizing Flows.

Christina Winkler, Daniel E. Worrall, Emiel Hoogeboom, Max Welling

CoRR, 2019

Affine Self Convolution.

Nichita Diaconu, Daniel E. Worrall

CoRR, 2019

Uncertainty Quantification in Deep Learning for Safer Neuroimage Enhancement.

Ryutaro Tanno, Daniel E. Worrall, Enrico Kaden, Aurobrata Ghosh, Francesco Grussu, Alberto Bizzi, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander

CoRR, 2019

Deep Scale-spaces: Equivariance Over Scale.

Daniel E. Worrall, Max Welling

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Supervised Uncertainty Quantification for Segmentation with Multiple Annotations.

Shi Hu, Daniel E. Worrall, Stefan Knegt, Bas Veeling, Henkjan J. Huisman, Max Welling

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019

Learning to Convolve: A Generalized Weight-Tying Approach.

Nichita Diaconu, Daniel E. Worrall

Proceedings of the 36th International Conference on Machine Learning, 2019

Reversible GANs for Memory-Efficient Image-To-Image Translation.

Tycho F. A. van der Ouderaa, Daniel E. Worrall

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2019

2018

CubeNet: Equivariance to 3D Rotation and Translation.

Daniel E. Worrall, Gabriel J. Brostow

Proceedings of the Computer Vision - ECCV 2018, 2018

2017

Virtual Adversarial Ladder Networks For Semi-supervised Learning.

Saki Shinoda, Daniel E. Worrall, Gabriel J. Brostow

CoRR, 2017

Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution.

Ryutaro Tanno, Daniel E. Worrall, Aurobrata Ghosh, Enrico Kaden, Stamatios N. Sotiropoulos, Antonio Criminisi, Daniel C. Alexander

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017

Interpretable Transformations with Encoder-Decoder Networks.

Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov, Gabriel J. Brostow

Proceedings of the IEEE International Conference on Computer Vision, 2017

Harmonic Networks: Deep Translation and Rotation Equivariance.

Daniel E. Worrall, Stephan J. Garbin, Daniyar Turmukhambetov, Gabriel J. Brostow

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks.

Daniel E. Worrall, Clare M. Wilson, Gabriel J. Brostow

Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016