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...
المؤلف الرئيسي: | Lienart, T |
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مؤلفون آخرون: | Doucet, A |
التنسيق: | أطروحة |
اللغة: | English |
منشور في: |
2017
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الموضوعات: |
مواد مشابهة
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Neural networks for inference, inference for neural networks
حسب: Webb, S
منشور في: (2018) -
Piecewise-deterministic Markov chain Monte Carlo
حسب: Vanetti, P
منشور في: (2019) -
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions
حسب: Samuel Livingstone, وآخرون
منشور في: (2014-06-01) -
Bayesian inference with geodetic applications /
حسب: 253571 Koch, Karl-Rudolf, وآخرون
منشور في: (1990) -
The predictive view of Bayesian inference
حسب: Fong, CHE
منشور في: (2021)