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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
On rooted trees and differentiation
The chain rule for higher order derivatives boosts a wealth of beautiful mathematical structure touching the theory of special rooted trees, group theory, combinatorics of integer partitions, order theory, and many others.
Dual numbers
I found writing this next post is a real treat. It’s about dual numbers. Dual numbers are a bit strange, to say the least, and at first they seem like an abstract mathematical fancy, but as you will see they have quite a useful purpose in the realm of automatic differentiation.
Reversible optimisers
Reversible neural architectures have been a popular research area in the last few years, but reversibility is also built into many modern day neural optimisers, perhaps serendipitously.
On the ‘invention’ of randomness
Recently in AMLAB we started a Jaynes reading group. E T Jaynes’ posthumous book and general all-round cult classic Probability Theory: The Logic of Science is the focus of our study. After having lectured a Bayesian statistics course for the last two years…
publications
Automated Retinopathy of Prematurity Case Detection with Convolutional Neural Networks
Published in Deep Learning and Data Labeling for Medical Applications, Springer 2016
(Paper)
Harmonic Networks: Deep Translation and Rotation Equivariance
Daniel Worrall, Stephan Garbin, Daniyar Turmukhambetov, Gabriel Brostow
Published in CVPR 2017
(Paper)
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution
Ryutaro Tanno, Daniel Worrall, Aurobrata Ghosh, Enrico Kaden, Stamatios N Sotiropoulos, Antonio Criminisi, Daniel Alexander
Published in MICCAI 2017
(Paper)
Interpretable Transformations with Encoder-Decoder Networks
Daniel E Worrall, Stephan Garbin, Daniyar Turmukhambetov, Gabriel Brostow
Published in ICCV 2017
(Paper)
Virtual Adversarial Ladder Networks For Semi-supervised Learning
Saki Shinoda, Daniel E Worrall, Gabriel Brostow
Published in NIPS LLD Workshop 2017
(Paper)
CubeNet: Equivariance to 3D Rotation and Translation
Daniel E Worrall, Gabriel J Brostow
Published in ECCV 2018
(Paper)
Witnessing atrocities: quantifying villages destruction in Darfur with crowdsourcing and transfer learning
Julien Cornebise*, Daniel E Worrall*, Micah Farfour, Milena Marin
Published in NeurIPS AI for Social Good Workshop 2018
(Paper)
Reversible GANs for Memory-efficient Image-to-Image Translation
Tycho van der Ouderaa, Daniel E Worrall
Published in CVPR 2019
(Paper)
Learning to Convolve: A Generalized Weight-Tying Approach
Nichita Diaconu*, Daniel E Worrall*
Published in ICML 2019
(Paper)
Reversible GANs for Memory-efficient Chest CT Super-resolution and Domain-adaptation in 3D
Tycho van der Ouderaa, Daniel E Worrall
Published in MIDL 2019
(Paper)
Deep Scale-spaces: Equivariance Over Scale
Daniel E Worrall, Max Welling
Published in NeurIPS 2019
(Paper)
Supervised Uncertainty Quantification for Segmentation with Multiple Annotations
Shi Hu, Daniel E Worrall, Stefan Knegt, Bas Veeling, Henkjan Huisman, Max Welling
Published in MICCAI 2019
(Paper)
Affine Self Convolution
Nichita Diaconu*, Daniel E Worrall*
Published in Preprint 2019
(Paper)
Learning Likelihoods with Conditional Normalizing Flows
Christina Winkler, Daniel E Worrall, Emiel Hoogeboom, Max Welling
Published in Preprint 2019
(Paper)
SE(3)-Transformers: 3D Roto-Translation Equivariant Attention Networks
Fabian B Fuchs, Daniel E Worrall, Volker Fischer, Max Welling
Published in NeurIPS 2020
(Paper)
MDP Homomorphic Networks: Group Symmetries in Reinforcement Learning
Elise van der Pol, Daniel E Worrall, Herke van Hoof, Frans A Oliehoek, Max Welling
Published in NeurIPS 2020
(Paper)
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
Published in NeuroImage 2021
(Paper)
Message Passing Neural PDE Solvers
Johannes Brandstetter, Daniel E Worrall, Max Welling
Published in ICLR 2022
(Paper)
Lie Point Symmetry Data Augmentation for Neural PDE Solvers
Johannes Brandstetter, Max Welling, Daniel E Worrall
Published in Preprint 2022
(Paper)
Neural Simulated Annealing
Alvaro H.C. Correia, Daniel E. Worrall, Roberto Bondesan
Published in Preprint 2022
(Paper)
talks
teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
Teaching experience 2
Workshop, University 1, Department, 2015