Freddie Bickford Smith

Freddie Bickford Smith

Deep Learning, Uncertainty Estimation

I’m a DPhil student working with Tom Rainforth and Adam Foster. My research focuses on principled data acquisition for machine learning. I have also worked on an approximate-inference scheme to allow neural networks to learn more effectively across sequences of tasks. Previously, during my MSc at UCL, I collaborated with Brad Love, Brett Roads and Ed Grefenstette on a project aimed at understanding neural networks from a cognitive-science perspective. As an undergraduate I studied mechanical engineering at Bristol, working on carbon-fibre composites with Fabrizio Scarpa and on 3D printing with Ben Hicks.



  • F. Bickford Smith , A. Kirsch , S. Farquhar , Y. Gal , A. Foster , T. Rainforth , Prediction-oriented Bayesian active learning, International Conference on Artificial Intelligence and Statistics, 2023.
  • T. Rainforth , A. Foster , D. R. Ivanova , F. Bickford Smith , Modern Bayesian experimental design, Statistical Science (to appear), 2023.


  • T. G. J. Rudner , F. Bickford Smith , Q. Feng , Y. W. Teh , Y. Gal , Continual learning via sequential function-space variational inference, International Conference on Machine Learning, 2022.