
I am a Postdoc at the Cambridge Image Analysis group. My research interests include
- deep learning
- inverse problems
- invertible neural networks
- medical imaging (in particular high-dimensional 3D data)
- adversarial examples
Publications
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans
– Nature Machine Intelligence
(2021)
3,
199
(DOI: 10.1038/s42256-021-00307-0)
iUNets: Learnable Invertible Up- and Downsampling for Large-Scale Inverse Problems
– IEEE International Workshop on Machine Learning for Signal Processing, MLSP
(2020)
2020-September,
1
On the connection between adversarial robustness and saliency map interpretability
– 36th International Conference on Machine Learning, ICML 2019
(2019)
2019-June,
3255
Structure preserving deep learning
Equivariant neural networks for inverse problems
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein
Distance)