Results 41 to 50 of about 1,249,090 (302)
BMC Evolutionary Biology, 2005 Background Bayesian phylogenetic inference holds promise as an alternative to maximum likelihood, particularly for large molecular-sequence data sets.
Harlow Timothy J +2 more
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On Probability and Cosmology: Inference Beyond Data? [PDF]
, 2017 Modern scientific cosmology pushes the boundaries of knowledge and the knowable. This is prompting questions on the nature of scientific knowledge. A central issue is what defines a 'good' model.
Sahlen, Martin
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BMC Medical Research Methodology, 2020 Background Although null hypothesis significance testing (NHST) is the agreed gold standard in medical decision making and the most widespread inferential framework used in medical research, it has several drawbacks.
Riko Kelter
semanticscholar +1 more source
Bayesian inference for inverse problems [PDF]
, 2001 Traditionally, the MaxEnt workshops start by a tutorial day. This paper summarizes my talk during 2001'th workshop at John Hopkins University. The main idea in this talk is to show how the Bayesian inference can naturally give us all the necessary tools ...
Mohammad-Djafari, Ali
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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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A Design Methodology for Fault-Tolerant Neuromorphic Computing Using Bayesian Neural Network
Micromachines, 2023 Memristor crossbar arrays are a promising platform for neuromorphic computing. In practical scenarios, the synapse weights represented by the memristors for the underlying system are subject to process variations, in which the programmed weight when read
Di Gao, Xiaoru Xie, Dongxu Wei
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Fuzzy Bayesian Inference [PDF]
, 2009 Data are frequently not precise numbers but more or less non-precise, also called fuzzy. Moreover a-priori information in Bayesian inference is usually not available as a precise probability distribution. In case of fuzzy data and fuzzy a-priori information Bayes' theorem has to be generalized.
openaire +2 more sources
BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis
bioRxiv, 2018 Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data.
R. Bouckaert +24 more
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Massively parallel Bayesian inference for transient gravitational-wave astronomy
Monthly notices of the Royal Astronomical Society, 2020 Understanding the properties of transient gravitational waves (GWs) and their sources is of broad interest in physics and astronomy. Bayesian inference is the standard framework for astrophysical measurement in transient GW astronomy.
Rory J. E. Smith +3 more
semanticscholar +1 more source
On adaptive Bayesian inference
, 2008 We study the rate of Bayesian consistency for hierarchical priors consisting of prior weights on a model index set and a prior on a density model for each choice of model index.
Xing, Yang
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