scientific article; zbMATH DE number 7164700
From MaRDI portal
Publication:5214185
zbMath1441.62927arXiv1708.00955MaRDI QIDQ5214185
Robert Kohn, Khue-Dung Dang, Minh-Ngoc Tran, Matias Quiroz, Mattias Villani
Publication date: 7 February 2020
Full work available at URL: https://arxiv.org/abs/1708.00955
Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Markov chain Monte CarloBayesian inferencebig dataestimated likelihoodstochastic gradient Langevin dynamicsstochastic gradient Hamiltonian Monte Carlo
Bayesian inference (62F15) Monte Carlo methods (65C05) Stochastic approximation (62L20) Statistical aspects of big data and data science (62R07)
Related Items
Stochastic gradient Hamiltonian Monte Carlo for non-convex learning, The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC, An Approach to Incorporate Subsampling Into a Generic Bayesian Hierarchical Model, Distributed computation for marginal likelihood based model choice, Physics-informed information field theory for modeling physical systems with uncertainty quantification, Subsampling sequential Monte Carlo for static Bayesian models, Subsampling MCMC -- an introduction for the survey statistician, Laplacian Smoothing Stochastic Gradient Markov Chain Monte Carlo
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- The pseudo-marginal approach for efficient Monte Carlo computations
- The Correlated Pseudo-Marginal Method
- The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
- The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data
- On some properties of Markov chain Monte Carlo simulation methods based on the particle filter
- General state space Markov chains and MCMC algorithms
- Langevin diffusions and Metropolis-Hastings algorithms
- Merging MCMC subposteriors through Gaussian-process approximations
- Normalizing constants of log-concave densities
- On Russian roulette estimates for Bayesian inference with doubly-intractable likelihoods
- Subsampling sequential Monte Carlo for static Bayesian models
- Subsampling MCMC -- an introduction for the survey statistician
- Informed sub-sampling MCMC: approximate Bayesian inference for large datasets
- Control variates for stochastic gradient MCMC
- On the efficiency of pseudo-marginal random walk Metropolis algorithms
- On nonnegative unbiased estimators
- Optimal tuning of the hybrid Monte Carlo algorithm
- (Non-) asymptotic properties of Stochastic Gradient Langevin Dynamics
- Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
- Optimal Scaling of Discrete Approximations to Langevin Diffusions
- Riemann Manifold Langevin and Hamiltonian Monte Carlo Methods
- Robust and Scalable Bayes via a Median of Subset Posterior Measures
- Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods
- Equation of State Calculations by Fast Computing Machines
- Speeding Up MCMC by Efficient Data Subsampling
- Efficient implementation of Markov chain Monte Carlo when using an unbiased likelihood estimator
- Particle Metropolis-adjusted Langevin algorithms
- Monte Carlo sampling methods using Markov chains and their applications
- A Stochastic Approximation Method