Search Results for author: Freddie Bickford Smith

Found 5 papers, 3 papers with code

Continual Learning via Sequential Function-Space Variational Inference

no code implementations28 Dec 2023 Tim G. J. Rudner, Freddie Bickford Smith, Qixuan Feng, Yee Whye Teh, Yarin Gal

Sequential Bayesian inference over predictive functions is a natural framework for continual learning from streams of data.

Bayesian Inference Continual Learning +2

Prediction-Oriented Bayesian Active Learning

1 code implementation17 Apr 2023 Freddie Bickford Smith, Andreas Kirsch, Sebastian Farquhar, Yarin Gal, Adam Foster, Tom Rainforth

Information-theoretic approaches to active learning have traditionally focused on maximising the information gathered about the model parameters, most commonly by optimising the BALD score.

Active Learning

Modern Bayesian Experimental Design

no code implementations28 Feb 2023 Tom Rainforth, Adam Foster, Desi R Ivanova, Freddie Bickford Smith

Bayesian experimental design (BED) provides a powerful and general framework for optimizing the design of experiments.

Experimental Design

Understanding top-down attention using task-oriented ablation design

1 code implementation8 Jun 2021 Freddie Bickford Smith, Brett D Roads, Xiaoliang Luo, Bradley C Love

Then on each task we compare the performance of two neural networks, one with top-down attention and one without.

Cannot find the paper you are looking for? You can Submit a new open access paper.