Staff profile

I am a PhD student in Computer Science at Durham University. My research is in the field of deep learning with a focus on unsupervised learning, generative modelling, probabilistic modelling, and machine reasoning.

• Deep Learning
• Generative Models
• Machine Reasoning

Conference Paper

• Bond-Taylor, S.E., Hessey, P., Sasaki, H., Breckon, T.P. & Willcocks, C.G. (2022), Unleashing Transformers: Parallel Token Prediction with Discrete Absorbing Diffusion for Fast High-Resolution Image Generation from Vector-Quantized Codes, Proc. European Conference on Computer Vision. Tel Aviv, Israel, Springer.
• Corona-Figueroa, Abril, Frawley, Jonathan, Bond-Taylor, Sam, Bethapudi, Sarath, Shum, Hubert P. H. & Willcocks, Chris G. (2022), MedNeRF: Medical Neural Radiance Fields for Reconstructing 3D-aware CT-Projections from a Single X-ray, 2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). Glasgow, Scotland, 3843-3848.
• Bond-Taylor, Sam & Willcocks, Chris G. (2021), Gradient Origin Networks, International Conference on Learning Representations. Vienna / Virtual.
• Leach, Adam, Rudden, Lucas S.P., Bond-Taylor, Sam, Brigham, John C., Degiacomi, Matteo T. & Willcocks, Chris G. (2020), Shape tracing: An extension of sphere tracing for 3D non-convex collision in protein docking, 2020 IEEE 20th International Conference on Bioinformatics and Bioengineering (BIBE). 49-52.

Journal Article

• Bond-Taylor, Sam, Leach, Adam, Long, Yang & Willcocks, Chris G. (2022). Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models. IEEE Transactions on Pattern Analysis and Machine Intelligence 44(11): 7327 - 7347.