The perceptual boost of visual attention is task-dependent in naturalistic settings. - Freddie Bickford Smith; Xiaoliang Luo; Brett D. Roads; Bradley C. Love (CoRR, 2020)

Understanding top-down attention using task-oriented ablation design. - Freddie Bickford Smith; Brett D. Roads; Xiaoliang Luo; Bradley C. Love (CoRR, 2021)

Continual Learning via Sequential Function-Space Variational Inference. - Tim G. J. Rudner; Freddie Bickford Smith; Qixuan Feng; Yee Whye Teh; Yarin Gal (ICML, 2022)

Prediction-Oriented Bayesian Active Learning. - Freddie Bickford Smith; Andreas Kirsch 002; Sebastian Farquhar; Yarin Gal; Adam Foster 001; Tom Rainforth (AISTATS, 2023)

Modern Bayesian Experimental Design. - Tom Rainforth; Adam Foster 001; Desi R. Ivanova; Freddie Bickford Smith (CoRR, 2023)

Making Better Use of Unlabelled Data in Bayesian Active Learning. - Freddie Bickford Smith; Adam Foster 001; Tom Rainforth (AISTATS, 2024)

Rethinking Aleatoric and Epistemic Uncertainty. - Freddie Bickford Smith; Jannik Kossen; Eleanor Trollope; Mark van der Wilk; Adam Foster 001; Tom Rainforth (CoRR, 2024)

Prediction-Oriented Subsampling from Data Streams. - Benedetta Lavinia Mussati; Freddie Bickford Smith; Tom Rainforth; Stephen Roberts 001 (CoRR, 2025)

Scaling Up Active Testing to Large Language Models. - Gabrielle Berrada; Jannik Kossen; Muhammed Razzak; Freddie Bickford Smith; Yarin Gal; Tom Rainforth (CoRR, 2025)