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The following pages link to Langevin-type models. I: Diffusions with given stationary distributions and their discretizations (Q1961832):

Displaying 35 items.

Langevin diffusions on the torus: estimation and applications (Q122538) (← links)
Stability of partially implicit Langevin schemes and their MCMC variants (Q429995) (← links)
Convergence rate of weak local linearization schemes for stochastic differential equations with additive noise (Q482674) (← links)
Subgeometric ergodicity of strong Markov processes (Q558691) (← links)
A note on convergence rate of a linearization method for the discretization of stochastic differential equations (Q718587) (← links)
Ergodicity and exponential \(\beta\)-mixing bounds for multidimensional diffusions with jumps (Q873605) (← links)
Metropolis-Hastings algorithms with acceptance ratios of nearly 1 (Q904057) (← links)
Subgeometric rates of convergence of \(f\)-ergodic strong Markov processes (Q1009672) (← links)
Accelerating Gaussian diffusions (Q1308710) (← links)
Langevin diffusions and Metropolis-Hastings algorithms (Q1398011) (← links)
\(V\)-subgeometric ergodicity for a Hastings-Metropolis algorithm (Q1587711) (← links)
Weighted multilevel Langevin simulation of invariant measures (Q1634175) (← links)
Convergent stochastic expectation maximization algorithm with efficient sampling in high dimension. Application to deformable template model estimation (Q1663188) (← links)
f-SAEM: a fast stochastic approximation of the EM algorithm for nonlinear mixed effects models (Q2008004) (← links)
Stochastic zeroth-order discretizations of Langevin diffusions for Bayesian inference (Q2137043) (← links)
On sampling from a log-concave density using kinetic Langevin diffusions (Q2174987) (← links)
User-friendly guarantees for the Langevin Monte Carlo with inaccurate gradient (Q2280028) (← links)
Non-asymptotic guarantees for sampling by stochastic gradient descent (Q2290072) (← links)
Ergodicity of the zigzag process (Q2330462) (← links)
On the computational complexity of MCMC-based estimators in large samples (Q2388988) (← links)
Weak local linear discretizations for stochastic differential equations: convergence and numerical schemes (Q2433776) (← links)
Langevin diffusions and the Metropolis-adjusted Langevin algorithm (Q2453987) (← links)
Stationarity preserving and efficiency increasing probability mass transfers made possible (Q2463660) (← links)
Langevin type limiting processes for adaptive MCMC (Q2520143) (← links)
Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise. (Q2574509) (← links)
Polynomial ergodicity of Markov transition kernels. (Q2574534) (← links)
Proximal Markov chain Monte Carlo algorithms (Q2628880) (← links)
(Q4999096) (← links)
(Q5011285) (← links)
A Variational Characterization of Langevin-Smoluchowski Diffusions (Q5050087) (← links)
Scaling Limits for the Transient Phase of Local Metropolis–Hastings Algorithms (Q5313588) (← links)
Bayesian computation: a summary of the current state, and samples backwards and forwards (Q5963784) (← links)
Exact targeting of Gibbs distributions using velocity-jump processes (Q6054237) (← links)
Strong invariance principles for ergodic Markov processes (Q6200877) (← links)
NF-ULA: normalizing flow-based unadjusted Langevin algorithm for imaging inverse problems (Q6556790) (← links)