Variational Bayesian optimal experimental design
Bayesian optimal experimental design (BOED) is a principled framework for making efficient use of limited experimental resources. Unfortunately, its applicability is hampered by the difficulty of obtaining accurate estimates of the expected information gain (EIG) of an experiment. To address this, w...
Main Authors: | Foster, A, Jankowiak, M, Bingham, E, Horsfall, P, Tee, YW, Rainforth, T, Goodman, N |
---|---|
Format: | Conference item |
Izdano: |
Conference on Neural Information Processing Systems
2019
|
Podobne knjige/članki
-
A unified stochastic gradient approach to designing Bayesian-optimal experiments
od: Foster, A, et al.
Izdano: (2020) -
Modern Bayesian experimental design
od: Rainforth, T, et al.
Izdano: (2024) -
Variational, Monte Carlo and policy-based approaches to Bayesian experimental design
od: Foster, AE
Izdano: (2021) -
Making better use of unlabelled data in Bayesian Active learning
od: Bickford Smith, F, et al.
Izdano: (2024) -
Bayesian Optimization for Probabilistic Programs
od: Rainforth, T, et al.
Izdano: (2016)