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Chris G. Willcocks Associate Professor Department of Computer Science Durham University Office: MCS 2026 |
Research
Research in unsupervised deep generative models and machine reasoning. Here is a list of publications and a link to scholar. For recent news please visit my twitter profile, and for software updates visit github.
Highlights
- Bond-Taylor, S., & Willcocks, C. G. (2023). ∞-diff: infinite resolution diffusion with subsampled mollified states. arXiv preprint arXiv:2303.18242. URL: https://arxiv.org/abs/2303.18242
- Bond-Taylor, S., Leach, A., Long, Y., & Willcocks, C. G. (2021). Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models. IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 1–1. doi:10.1109/TPAMI.2021.3116668
- Corona-Figueroa, A., Bond-Taylor, S., Bhowmik, N., Gaus, Y. F. A., Breckon, T. P., Shum, H. P., & Willcocks, C. G. (2023). Unaligned 2D to 3D Translation with Conditional Vector-Quantized Code Diffusion using Transformers. Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 14585–14594). URL: https://abrilcf.github.io/publications/CodeDiff3D/
- Bond-Taylor, S., & Willcocks, C. G. (2021). Gradient Origin Networks. International Conference on Learning Representations (ICLR). URL: https://openreview.net/pdf?id=0O_cQfw6uEh
- Leach, A., Schmon, S. M., Degiacomi, M. T., & Willcocks, C. G. (2022). Denoising Diffusion Probabilistic Models on SO(3) for Rotational Alignment. ICLR 2022 Workshop on Geometrical and Topological Representation Learning. URL: https://openreview.net/forum?id=BY88eBbkpe5
Teaching
I teach the year three deep learning and reinforcement learning modules, alongside the year two ‘cyber security’ submodule. Slides and other material are available in the teaching section. Past teaching:
- Deep Learning (2019-present)
- Reinforcement Learning (2020-present)
- Cyber Security (2017-present)
- Machine Learning (2018)
Biography
I am an Associate Professor in Computer Science at Durham University and a member of the Scientific Computing and VIVID groups. My research is in theoretical areas of deep learning, specifically looking at deep generative models. Previously, I co-founded and led as CTO a Durham University startup that deploys large-scale AI models. I am an area chair for BMVC and also the admissions tutor for computer science. I am a reviewer for the EU Commission, CVPR, and IEEE including TPAMI, TIFS, TNNLS, TIP and TMI.
Professional Activities
- Admissions tutor (2021-present).
- Fellowship of the HEA (FHEA).
- Area Chair of BMVC 2023.
- Invited speaker at Chinese University of Hong Kong (CUHK), 2023.
- Invited speaker at National DICE Conference (2023).
- Invited speaker at BMVA 2022 Summer School (slides).
- Open Day coordinator (2021-2022).
- Area Chair of BMVC 2021.
- Invited speaker at 2020 Cyber Operational Conference on ‘Meta learning: Smart Interfacing’.
- Area Chair of BMVA 2020 Conference.
- Participating scientist on Scientist Next Door (SND).
- Invited speaker at Chinese University of Hong Kong (CUHK), 13th Aug 2019.
- Chair of BMVA symposium of ‘Deep Learning in 3-Dimensions’, 20th Feb 2019.
- Speaker on BBC Sunday Politics discussing Cyber Security spending in public bodies.
- Invited to present at Durham Celebrating Excellence research exhibition.
- Member of W3C Web Assembly.
- Reviewer for CVPR.
- Reviewer for EU Commission.
- Reivewer for IEEE Transactions on Information Forensics & Security.
- Reivewer for IEEE Transactions on Medical Imaging.
- Reivewer for IEEE Transactions on Image Processing.
- Reviewer for IEEE Transactions on Pattern Analysis and Machine Intelligence.
- Reviewer for IEEE Transactions on Neural Networks and Learning Systems .
- Reviewer for Journal of Real-Time Image Processing
- Member of Scientific Computing research group.
If you like maths and rain, you may like this relaxing interactive visualisation that I made. You can play rain sound and control it with the: F, P, S, M and X keys.
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