I am a Postdoc at the Cambridge Image Analysis group. My research interests include
- inverse problems
- neural networks with mathematical guarantees
- medical imaging (in particular high-dimensional 3D data)
- adversarial examples
- structure preserving deep learning
Publications
Equivariant neural networks for inverse problems
– Inverse Problems
(2021)
(DOI: 10.1088/1361-6420/ac104f)
Structure-preserving deep learning
– European Journal of Applied Mathematics
(2021)
1
(DOI: 10.1017/S0956792521000139)
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
– PROCEEDINGS OF THE 2020 IEEE 30TH INTERNATIONAL WORKSHOP ON MACHINE LEARNING FOR SIGNAL PROCESSING (MLSP)
(2020)
00,
1
On the connection between adversarial robustness and saliency map interpretability
– 36th International Conference on Machine Learning, ICML 2019
(2019)
2019-June,
3255
Wasserstein GANs Work Because They Fail (to Approximate the Wasserstein
Distance)