Standard approaches for Bayesian inference focus solely on approximating the posterior distribution. Typically, this approximation is, in turn, used to�...
Finally, in Section 6, we show how the TABI framework can be applied to any marginal likelihood estimator to produce a target–aware inference scheme,�...
Jan 1, 2020 � We address this inefficiency by introducing a framework for target-aware Bayesian inference (TABI) that estimates these expectations directly.
Apr 24, 2023 � In this work, we introduce a generalized thermodynamic integration (GTI) scheme which is able to perform a target-aware Bayesian inference.
Target–aware Bayesian inference: how to beat optimal conventional estimators. T Rainforth*, A Goliński*, F Wood, S Zaidi. Journal of Machine Learning Research�...
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Jun 21, 2022 � Target–Aware Bayesian Inference: How to Beat. Optimal Conventional Estimators. Journal of Machine. Learning Research, 21(88):1–54, 2020�...
Zaidi, “Target–Aware Bayesian Inference: How to Beat the Optimal Conventional Monte Carlo Estimator,” Journal of Machine Learning Research (JMLR), 2020.
In this paper, we focus on the computation of the posterior expectation of a function f ( x ) . We consider a target-aware scenario where f ( x ) is known in�...
Target–Aware Bayesian Inference: How to Beat Optimal Conventional Estimators. Tom Rainforth, Adam Golinski, Frank Wood, Sheheryar Zaidi (88):1−54, 2020 code�...
Apr 7, 2023 � In this work, we introduce a generalized thermodynamic integration (GTI) scheme which is able to perform a target-aware Bayesian inference, i.e.�...