Christopher Williams
College Lecturer in Mathematics (Probability and Statistics)
Christopher is a computational mathematician specialising in the development of statistical methodologies and numerical methods, with applications in scientific computing. His research focuses on developing provably stable and accurate algorithms, ensuring their robustness when applied to these complex scientific challenges. Currently, his interests lie in generative modelling, Monte Carlo methods, inverse problems, and numerical solutions to partial differential equations (PDEs).
Selected publications are:
Score-Optimal Diffusion Schedules
C. Williams, A. Campbell, A. Doucet, S. Syed
Advances in Neural Information Processing Systems (NeurIPS) 38, 2024
Full-Spectrum Dispersion Relation Preserving Summation-by-Parts Operators
C. Williams, K. Duru
SIAM Journal on Numerical Analysis 62 (4), 1565-1588, 2024
A Unified Framework for U-Net Design and Analysis
C. Williams*, F. Falck*, G. Deligiannidis, C.C. Holmes, A. Doucet, S. Syed
Advances in Neural Information Processing Systems (NeurIPS) 37, 27745-27782, 2023
Dispersion Relation Preserving FD Schemes and Self-Affine DG Elements
C.J. Williams
The Australian National University, 2021
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