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Bayesian statistical inference
Statistica, 2017 This work was translated into English and published in the volume: Bruno De Finetti, Induction and Probability, Biblioteca di Statistica, eds. P. Monari, D.
Bruno De Finetti
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Discussion points for Bayesian inference [PDF]
Nature Human Behaviour, 2020 Despite its many advocates, Bayesian inference is currently employed by only a minority of social and behavioural scientists. One possible barrier is a lack of consensus on how best to conduct and report such analyses. Employing Bayesian methods involves making choices about prior distributions, likelihood functions and robustness checks, as well as ...
B. Aczél +11 more
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Robust generalised Bayesian inference for intractable likelihoods [PDF]
Journal of the Royal Statistical Society: Series B (Statistical Methodology), 2021 Generalised Bayesian inference updates prior beliefs using a loss function, rather than a likelihood, and can therefore be used to confer robustness against possible mis‐specification of the likelihood.
Takuo Matsubara +3 more
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Connecting the free energy principle with quantum cognition
Frontiers in Neurorobotics, 2022 It appears that the free energy minimization principle conflicts with quantum cognition since the former adheres to a restricted view based on experience while the latter allows deviations from such a restricted view.
Yukio-Pegio Gunji +2 more
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On Sequential Bayesian Inference for Continual Learning
Entropy, 2023 Sequential Bayesian inference can be used for continual learning to prevent catastrophic forgetting of past tasks and provide an informative prior when learning new tasks.
Samuel Kessler +4 more
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Bayesian inference for compact binary coalescences with bilby: validation and application to the first LIGO–Virgo gravitational-wave transient catalogue [PDF]
Monthly notices of the Royal Astronomical Society, 2020 Gravitational waves provide a unique tool for observational astronomy. While the first LIGO–Virgo catalogue of gravitational-wave transients (GWTC-1) contains 11 signals from black hole and neutron star binaries, the number of observations is ...
I. Romero-Shaw +62 more
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Adaptive User Interfaces and the Use of Inference Methods
Computational Science and Techniques, 2021 Bayesian Networks are used to model a user's behaviour. There is not much research on the use of Frequentist Inference to accomplish this same task.
Rachelle Barrette, Ratvinder Grewal
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Synaptic plasticity as Bayesian inference [PDF]
Nature Neuroscience, 2021 Published in Nature Neuroscience: https://www.nature.com/articles/s41593-021-00809 ...
Laurence Aitchison +8 more
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On the Geometry of Bayesian Inference [PDF]
Bayesian Analysis, 2019 We provide a geometric interpretation to Bayesian inference that allows us to introduce a natural measure of the level of agreement between priors, likelihoods, and posteriors. The starting point for the construction of our geometry is the simple observation that the marginal likelihood can be regarded as an inner product between the prior and the ...
de Carvalho, Miguel +2 more
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Randomization-based, Bayesian inference of causal effects
Journal of Causal Inference, 2023 Bayesian causal inference in randomized experiments usually imposes model-based structure on potential outcomes. Yet causal inferences from randomized experiments are especially credible because they depend on a known assignment process, not a ...
Leavitt Thomas
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