Exploiting low dimensional models in sensing, computation and signal processing

Davies, Michael (Principal Investigator)

School of Engineering

Status	Finished
Effective start/end date	1/09/16 → 31/08/22

Funding

EU government bodies: £1,474,699.00

20 Article
19 Conference contribution
11 Paper
9 Working paper
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Sensing Theorems for Unsupervised Learning in Linear Inverse Problems
Tachella, J., Chen, D. & Davies, M. E., 23 Jan 2023, (E-pub ahead of print) In: Journal of Machine Learning Research. 24, 45 p.
Research output: Contribution to journal › Article › peer-review

Open Access
File
Imaging with Equivariant Deep Learning: From unrolled network design to fully unsupervised learning
Chen, D., Davies, M., Ehrhardt, M. J., Schönlieb, C-B., Sherry, F. & Tachella, J., 2 Jan 2023, (E-pub ahead of print) In: IEEE Signal Processing Magazine. 40, 1, p. 134 - 147
Research output: Contribution to journal › Article › peer-review

Open Access
File
Robust Equivariant Imaging: a fully unsupervised framework for learning to image from noisy and partial measurements
Chen, D., Tachella, J. & Davies, M. E., 27 Sep 2022, (E-pub ahead of print) 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE Xplore, p. 5637-5646 (Conference on Computer Vision and Pattern Recognition (CVPR) ).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
File

Best Student Paper ICASSP 2022
Tachella, Julián (Recipient), Sheehan, Mikey (Recipient) & Davies, Michael (Recipient), 27 May 2022
Prize: Prize (including medals and awards)