Noname manuscript No. (will be inserted by the editor) k-Optimal: A Novel Approximate Inference Algorithm for ProbLog

Source URL: lirias.kuleuven.be

Approximate Inference Algorithms for Hybrid Bayesian Networks with Discrete Constraints Vibhav Gogate and Rina Dechter Donald Bren School of Information and Computer Science University of California, Irvine, CA 92967

Source URL: www.hlt.utdallas.edu

Hashing-Based Approximate Probabilistic Inference in Hybrid Domains Vaishak Belle Dept. of Computer Science KU Leuven Belgium

Source URL: lirias.kuleuven.be

arXiv:1401.2838v1 [cs.LG] 13 JanGPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation Max Welling

Source URL: www.ics.uci.edu

• Statistical inference
• Econometrics
• Confidence interval
• Measurement
• Marginal likelihood
• Likelihood function
• Normal distribution
• Markov chain
• Maximum likelihood
• Statistics
• Estimation theory
• Bayesian statistics

Exploiting Inference for Approximate Parameter Learning in Discriminative Fields: An Empirical Study Sanjiv Kumar, Jonas August, and Martial Hebert The Robotics Institute, Carnegie Mellon University Pittsburgh, PA 15213

Source URL: www.sanjivk.com

• Graphical models
• Bayesian statistics
• Probability theory
• Maximum likelihood
• Likelihood function
• Conditional random field
• Belief propagation
• Statistics
• Estimation theory
• M-estimators

Approximate Bayesian Inference for Hierarchical Gaussian Markov Random Fields Models H˚ avard Rue and Sara Martino Department of Mathematical Sciences NTNU, Norway

Source URL: www.math.ntnu.no

NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET Approximate Inference for Hierarchical Gaussian Markov Random Fields Models by

Source URL: www.math.ntnu.no

NORGES TEKNISK-NATURVITENSKAPELIGE UNIVERSITET Approximate Inference for Hierarchical Gaussian Markov Random Fields Models by

Source URL: www.math.ntnu.no

Approximative Bayesian inference Approximate Bayesian inference for latent Gaussian models H˚ avard Rue1

Source URL: www.bias-project.org.uk

Stochastic Backpropagation and Approximate Inference in Deep Generative Models

Source URL: machinelearning.wustl.edu