An Introduction to MCMC for Machine Learning

2003/01/01 by Christophe Andrieu, Nando de Freitas, Arnaud Doucet +1 · 4 citations
Computer Science · #Bayesian Methods and Mixture Models #Data Management and Algorithms #Gaussian Processes and Bayesian Inference

paper · pdf · doi:10.1023/a:1020281327116

crossref issued 2003/01/01 · crossref published 2003/01/01 · crossref published-print 2003/01/01 · openalex publication_date 2003/01/01 · crossref created 2003/03/15 · openalex created_date 2016/06/24 · crossref deposited 2025/07/10 · crossref indexed 2026/07/31 · openalex updated_date 2026/08/01

Citations

• Lattice Particle Filters
• Metropolis light transport
• Videovigilancia de altura
• Equation of State Calculations by Fast Computing Machines
• A random polynomial-time algorithm for approximating the volume of convex bodies
• A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
• Bayesian Density Estimation and Inference Using Mixtures
• Novel approach to nonlinear/non-Gaussian Bayesian state estimation
• Bayesian Analysis of Binary and Polychotomous Response Data
• Monte Carlo Inference via Greedy Importance Sampling
• On Gibbs sampling for state space models
• On sequential Monte Carlo sampling methods for Bayesian filtering
• Monte Carlo sampling methods using Markov chains and their applications
• Reversible Jump MCMC Simulated Annealing for Neural Networks
• Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks
• Sampling-Based Approaches to Calculating Marginal Densities

Cited by

• A Langevin sampling algorithm inspired by the Adam optimizer
• Solution to the galactic foreground problem for LISA
• From Blickets to Synapses: Inferring Temporal Causal Networks by Observation
• Klára Dán von Neumann [wikipedia]