Pages that link to "Item:Q2574509"

The following pages link to Ergodicity for SDEs and approximations: locally Lipschitz vector fields and degenerate noise. (Q2574509):

Displaying 50 items.

• Divergence of the backward Euler method for ordinary stochastic differential equations (Q2009062) (← links)
• Asymptotic log-Harnack inequality and applications for stochastic systems of infinite memory (Q2010491) (← links)
• Scaling limits for the generalized Langevin equation (Q2022593) (← links)
• Parametric inference for hypoelliptic ergodic diffusions with full observations (Q2023472) (← links)
• Large deviations of empirical measures of diffusions in weighted topologies (Q2024505) (← links)
• Gamma calculus beyond Villani and explicit convergence estimates for Langevin dynamics with singular potentials (Q2036641) (← links)
• Time-periodic measures, random periodic orbits, and the linear response for dissipative non-autonomous stochastic differential equations (Q2042083) (← links)
• Ergodic numerical approximation to periodic measures of stochastic differential equations (Q2043202) (← links)
• The kinetic Fokker-Planck equation with general force (Q2044679) (← links)
• Two-scale coupling for preconditioned Hamiltonian Monte Carlo in infinite dimensions (Q2045410) (← links)
• On the mean field limit of the random batch method for interacting particle systems (Q2070421) (← links)
• Error bounds of the invariant statistics in machine learning of ergodic Itô diffusions (Q2077623) (← links)
• Trajectory fitting estimation for a class of SDEs with small Lévy noises (Q2083427) (← links)
• Ensemble Kalman inversion for sparse learning of dynamical systems from time-averaged data (Q2083640) (← links)
• The backward Euler-Maruyama method for invariant measures of stochastic differential equations with super-linear coefficients (Q2106211) (← links)
• Learning stochastic dynamics with statistics-informed neural network (Q2112526) (← links)
• Variance reduction for additive functionals of Markov chains via martingale representations (Q2114045) (← links)
• Linear response based parameter estimation in the presence of model error (Q2124896) (← links)
• ISALT: inference-based schemes adaptive to large time-stepping for locally Lipschitz ergodic systems (Q2129142) (← links)
• Hypocoercivity with Schur complements (Q2136419) (← links)
• Improved bounds for discretization of Langevin diffusions: near-optimal rates without convexity (Q2137032) (← links)
• The Euler scheme for stochastic differential equations with discontinuous drift coefficient: a numerical study of the convergence rate (Q2141948) (← links)
• A splitting method for SDEs with locally Lipschitz drift: illustration on the FitzHugh-Nagumo model (Q2143109) (← links)
• The stochastic \(\theta\) method for stationary distribution of stochastic differential equations with Markovian switching (Q2144133) (← links)
• The Smoluchowski-Kramers limits of stochastic differential equations with irregular coefficients (Q2145771) (← links)
• Split-step theta Milstein methods for SDEs with non-globally Lipschitz diffusion coefficients (Q2154871) (← links)
• Couplings for Andersen dynamics (Q2155520) (← links)
• Solving eigenvalue PDEs of metastable diffusion processes using artificial neural networks (Q2157080) (← links)
• An adaptively weighted stochastic gradient MCMC algorithm for Monte Carlo simulation and global optimization (Q2159413) (← links)
• Hypocoercivity of linear kinetic equations via Harris's theorem (Q2176172) (← links)
• A full-discrete exponential Euler approximation of the invariant measure for parabolic stochastic partial differential equations (Q2192616) (← links)
• Adaptive Euler-Maruyama method for SDEs with nonglobally Lipschitz drift (Q2192733) (← links)
• Bridging the gap between constant step size stochastic gradient descent and Markov chains (Q2196224) (← links)
• Towards mesoscopic ergodic theory (Q2198342) (← links)
• Classical Langevin dynamics derived from quantum mechanics (Q2211463) (← links)
• Ergodicity and spike rate for stochastic FitzHugh-Nagumo neural model with periodic forcing (Q2213642) (← links)
• On stochastic gradient Langevin dynamics with dependent data streams in the logconcave case (Q2214233) (← links)
• Controlled sequential Monte Carlo (Q2215764) (← links)
• Positive Harris recurrence for degenerate diffusions with internal variables and randomly perturbed time-periodic input (Q2229570) (← links)
• Weak backward error analysis for stochastic Hamiltonian systems (Q2273193) (← links)
• The tamed unadjusted Langevin algorithm (Q2274251) (← links)
• Diffusion maps tailored to arbitrary non-degenerate Itô processes (Q2278457) (← links)
• Tamed Runge-Kutta methods for SDEs with super-linearly growing drift and diffusion coefficients (Q2301441) (← links)
• Multi-level Monte Carlo methods for the approximation of invariant measures of stochastic differential equations (Q2302502) (← links)
• Spectral density-based and measure-preserving ABC for partially observed diffusion processes. An illustration on Hamiltonian SDEs (Q2302513) (← links)
• High-dimensional Bayesian inference via the unadjusted Langevin algorithm (Q2325343) (← links)
• On the geometric ergodicity of Hamiltonian Monte Carlo (Q2325354) (← links)
• Higher order Langevin Monte Carlo algorithm (Q2326072) (← links)
• Couplings and quantitative contraction rates for Langevin dynamics (Q2327938) (← links)
• A multiscale analysis of diffusions on rapidly varying surfaces (Q2344115) (← links)