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...
Váldodahkki: | Lienart, T |
---|---|
Eará dahkkit: | Doucet, A |
Materiálatiipa: | Oahppočájánas |
Giella: | English |
Almmustuhtton: |
2017
|
Fáttát: |
Geahča maid
-
Neural networks for inference, inference for neural networks
Dahkki: Webb, S
Almmustuhtton: (2018) -
Piecewise-deterministic Markov chain Monte Carlo
Dahkki: Vanetti, P
Almmustuhtton: (2019) -
Information-Geometric Markov Chain Monte Carlo Methods Using Diffusions
Dahkki: Samuel Livingstone, et al.
Almmustuhtton: (2014-06-01) -
Bayesian inference with geodetic applications /
Dahkki: 253571 Koch, Karl-Rudolf, et al.
Almmustuhtton: (1990) -
The predictive view of Bayesian inference
Dahkki: Fong, CHE
Almmustuhtton: (2021)