Results 11 to 20 of about 63,287 (274)
Psychophysical identity and free energy [PDF]
, 2020 An approach to implementing variational Bayesian inference in biological systems is considered, under which the thermodynamic free energy of a system directly encodes its variational free energy.
Kiefer, Alex B.
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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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Variational Bayesian EM for SLAM [PDF]
2015 IEEE 6th International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2015 Designing accurate, robust and cost-effective systems is an important aspect of the research on self-driving vehicles. Radar is a common part of many existing automotive solutions and it is robust to adverse weather and lighting conditions, as such it can play an important role in the design of a self-driving vehicle.
Maryam Fatemi +3 more
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Entropy, 2021 In this paper, variational sparse Bayesian learning is utilized to estimate the multipath parameters for wireless channels. Due to its flexibility to fit any probability density function (PDF), the Gaussian mixture model (GMM) is introduced to represent ...
Lingjin Kong +3 more
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Variational Bayesian Optimistic Sampling
CoRR, 2021 We consider online sequential decision problems where an agent must balance exploration and exploitation. We derive a set of Bayesian `optimistic' policies which, in the stochastic multi-armed bandit case, includes the Thompson sampling policy. We provide a new analysis showing that any algorithm producing policies in the optimistic set enjoys $\tilde ...
Brendan O'Donoghue, Tor Lattimore
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Frontiers in Genetics, 2021 Motivation: Genome-wide association studies (GWAS) have achieved remarkable success in identifying SNP-trait associations in the last decade. However, it is challenging to identify the mechanisms that connect the genetic variants with complex traits as ...
Yi Yang, Kar-Fu Yeung, Jin Liu
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Bayesian variational regularization on the ball
CoRR, 2021 We develop variational regularization methods which leverage sparsity-promoting priors to solve severely ill posed inverse problems defined on the 3D ball (i.e. the solid sphere). Our method solves the problem natively on the ball and thus does not suffer from discontinuities that plague alternate approaches where each spherical shell is considered ...
Matthew A. Price, Jason D. McEwen
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Variational Inference for Bayesian Bridge Regression
Statistics and Computing, 2022 Abstract The bridge approach for regularization of coefficients in regression models uses ℓα norm, with α ∈ (0, +∞), to define a penalization on large values of the regression coefficients. Particular cases include the lasso and ridge penalizations.
Carlos Tadeu Pagani Zanini +2 more
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A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction
G3: Genes, Genomes, Genetics, 2017 There are Bayesian and non-Bayesian genomic models that take into account G×E interactions. However, the computational cost of implementing Bayesian models is high, and becomes almost impossible when the number of genotypes, environments, and traits is ...
Osval A. Montesinos-López +7 more
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Scientific Reports, 2022 In this paper, the inverse problems of cardiac sources using analytical and probabilistic methods are solved and discussed. The standard Tikhonov regularization technique is solved initially to estimate the under-determined heart surface potentials from ...
Vikas R. Bhat +3 more
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