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Approximate Bayesian Inference [PDF]
Entropy, 2020 This is the Editorial article summarizing the scope of the Special Issue: Approximate Bayesian Inference.
Pierre Alquier
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MrBayes 3: Bayesian phylogenetic inference under mixed models [PDF]
Bioinform., 2003 MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models.
Fredrik Ronquist, John P. Huelsenbeck
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Bayesian Inference in Numerical Cognition: A Tutorial Using JASP
Journal of Numerical Cognition, 2020 Researchers in numerical cognition rely on hypothesis testing and parameter estimation to evaluate the evidential value of data. Though there has been increased interest in Bayesian statistics as an alternative to the classical, frequentist approach to ...
Thomas J. Faulkenberry +2 more
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Frontiers in Neuroinformatics, 2018 Recent debates about the conventional traditional threshold used in the fields of neuroscience and psychology, namely P < 0.05, have spurred researchers to consider alternative ways to analyze fMRI data.
Hyemin Han
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Universal Darwinism As a Process of Bayesian Inference
Frontiers in Systems Neuroscience, 2016 Many of the mathematical frameworks describing natural selection are equivalent to Bayes’ Theorem, also known as Bayesian updating. By definition, a process of Bayesian Inference is one which involves a Bayesian update, so we may conclude that these ...
John Oberon Campbell
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Bayesian Inference of Phylogeny and Its Impact on Evolutionary Biology [PDF]
Science, 2001 John P. Huelsenbeck +3 more
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Overview of Research on Bayesian Inference and Parallel Tempering [PDF]
Jisuanji kexue, 2023 Bayesian inference is one of the main problems in statistics.It aims to update the prior knowledge of the probability distribution model based on the observation data.For the posterior probability that cannot be observed or is difficult to directly ...
ZHAN Jin, WANG Xuefei, CHENG Yurong, YUAN Ye
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UltraNest - a robust, general purpose Bayesian inference engine [PDF]
Journal of Open Source Software, 2021 UltraNest is a general-purpose Bayesian inference package for parameter estimation and model comparison. It allows fitting arbitrary models specified as likelihood functions written in Python, C, C++, Fortran, Julia or R.
J. Buchner
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Bayesian causal inference: a critical review [PDF]
Philosophical Transactions of the Royal Society A, 2022 This paper provides a critical review of the Bayesian perspective of causal inference based on the potential outcomes framework. We review the causal estimands, assignment mechanism, the general structure of Bayesian inference of causal effects and ...
Fan-qun Li, Peng Ding, F. Mealli
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RL with KL penalties is better viewed as Bayesian inference [PDF]
Conference on Empirical Methods in Natural Language Processing, 2022 Reinforcement learning (RL) is frequently employed in fine-tuning large language models (LMs), such as GPT-3, to penalize them for undesirable features of generated sequences, such as offensiveness, social bias, harmfulness or falsehood.
Tomasz Korbak, Ethan Perez, C. Buckley
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