Inference on Markov random fields: methods and applications

Inference on Markov random fields: methods and applications

<p>This thesis considers the problem of performing inference on undirected graphical models with continuous state spaces. These models represent conditional independence structures that can appear in the context of Bayesian Machine Learning. In the thesis, we focus on computational methods and...

Cur síos iomlán

Sonraí bibleagrafaíochta
Príomhchruthaitheoir:	Lienart, T
Rannpháirtithe:	Doucet, A
Formáid:	Tráchtas
Teanga:	English
Foilsithe / Cruthaithe:	2017
Ábhair:	Computational statistics Machine learning Bayesian statistics

Míreanna comhchosúla

Neural networks for inference, inference for neural networks
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Piecewise-deterministic Markov chain Monte Carlo
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Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions
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Bayesian inference with geodetic applications /
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The predictive view of Bayesian inference
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A posterior probability approach for gene regulatory network inference in genetic perturbation data
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Understanding approximation for Bayesian inference in neural networks
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Large scale methods for kernels, causal inference and survival modelling
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Bayesian parametric inference /
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Markov chain Monte Carlo : stochastic simulation for Bayesian inference /
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An introduction to Bayesian inference and decision /
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A nonparametric Bayesian method of translating machine learning scores to probabilities in clinical decision support
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Scalable Bayesian methods for the analysis of neuroimaging data
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Global Coronal Magnetic Field Estimation Using Bayesian Inference
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On the properties of random feature methods
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Decision theory and Bayesian inference : Hypothesis testing 1; Hypothesis 2
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Statistical Inference in fMRI using Random Field Theory and resampling methods
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Perception as Bayesian inference /
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Bayesian decision problems and Markov chains /
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Empirical performance of simple statistical inference-type models with feature extraction in comparison to modern machine learning methods concerning regression and classification problems
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Bayesian Structure Learning and Sampling of Bayesian Networks with the R Package BiDAG
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Inference and applications of genetic relatedness in human populations
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Bayesian reasoning and machine learning /
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Similarity - based virtual screening using bayesian inference network for searching chemical database /
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Applied Bayesian modeling and causal inference from incomplete-data perspectives : an essential journey with Donald Rubins statistical family /
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Bayesian stratified random sampling using auxiliary information /
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Similarity - based virtual screening using bayesian inference network for searching chemical database [electronic resource] /
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Bayesian network technologies : applications and graphical models /
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Bayesian statistical inference
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Bayesian inference of Weibull distribution for right and interval censored data
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A Hierarchical Bayesian Framework for Inferring the Stellar Obliquity Distribution
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Likelihood-free Bayesian inference for dynamic, stochastic simulators in the social sciences
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A Web Simulator to Assist in the Teaching of Bayes’ Theorem
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Implementation of Traditional (S-R)-Based PM Method with Bayesian Inference
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Advanced mapping of environmental data : geostatistics, machine learning, and Bayesian maximum entropy /
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A fortiori Bayesian inference in psychological research
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Approximate Bayesian Inference
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Bayesian inference and maximum entropy methods in science and engineering : 25th International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, San Jose, California, 7-12 August 2005 /
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Approximation methods for efficient learning of bayesian networks /
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Applied Bayesian hierarchical methods /
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