The following pages link to Eric Moulines (Q217350):
Displaying 34 items.
- Efficient Bayesian Computation by Proximal Markov Chain Monte Carlo: When Langevin Meets Moreau (Q4686924) (← links)
- (Q4849431) (← links)
- (Q4852337) (← links)
- Robust estimation of the scale and of the autocovariance function of Gaussian short- and long-range dependent processes (Q4979097) (← links)
- Variance Reduction for Dependent Sequences with Applications to Stochastic Gradient MCMC (Q4995114) (← links)
- A Proximal Markov Chain Monte Carlo Method for Bayesian Inference in Imaging Inverse Problems: When Langevin Meets Moreau (Q5044995) (← links)
- On Stochastic Gradient Langevin Dynamics with Dependent Data Streams: The Fully Nonconvex Case (Q5162623) (← links)
- On the two-filter approximations of marginal smoothing distributions in general state-space models (Q5214997) (← links)
- Error Exponents for Neyman-Pearson Detection of a Continuous-Time Gaussian Markov Process From Regular or Irregular Samples (Q5273642) (← links)
- Stability of Stochastic Approximation under Verifiable Conditions (Q5317131) (← links)
- A semi-blind channel estimation technique based on second-order blind method for CDMA systems (Q5353865) (← links)
- On perturbed proximal gradient algorithms (Q5361273) (← links)
- Detecting Aircraft With a Low-Resolution Infrared Sensor (Q5372923) (← links)
- Estimating Long Memory in Volatility (Q5393932) (← links)
- Large sample behaviour of some well-known robust estimators under long-range dependence (Q5402580) (← links)
- On the use of sequential Monte Carlo methods for approximating smoothing functionals, with application to fixed parameter estimation (Q5427531) (← links)
- Limit theorems for weighted samples with applications to sequential Monte Carlo methods (Q5427542) (← links)
- Wavelet estimator of long-range dependent processes. (Q5933670) (← links)
- Adaptive estimation of the fractional differencing coefficient (Q5950041) (← links)
- On parallel implementation of sequential Monte Carlo methods: the island particle model (Q5962737) (← links)
- Quantitative bounds of convergence for geometrically ergodic Markov chain in the Wasserstein distance with application to the Metropolis adjusted Langevin algorithm (Q5963544) (← links)
- Stochastic variable metric proximal gradient with variance reduction for non-convex composite optimization (Q6172923) (← links)
- On Upper-Confidence Bound Policies for Non-Stationary Bandit Problems (Q6209630) (← links)
- Blocking Strategies and Stability of Particle Gibbs Samplers (Q6265879) (← links)
- On the two-filter approximations of marginal smoothing distributions in general state space models (Q6274016) (← links)
- Smoothness Estimation for Whittle-Mat\'ern Processes on Closed Riemannian Manifolds (Q6515679) (← links)
- Diffusion approximations and control variates for MCMC (Q6552608) (← links)
- Particle-based, rapid incremental smoother meets particle Gibbs (Q6554555) (← links)
- Probability and moment inequalities for additive functionals of geometrically ergodic Markov chains (Q6592137) (← links)
- Stochastic approximation beyond gradient for signal processing and machine learning (Q6603684) (← links)
- On geometric convergence for the Metropolis-adjusted Langevin algorithm under simple conditions (Q6637869) (← links)
- Central Limit Theorem for Bayesian Neural Network trained with Variational Inference (Q6732481) (← links)
- Probabilistic Conformal Prediction with Approximate Conditional Validity (Q6734778) (← links)
- A New Bound on the Cumulant Generating Function of Dirichlet Processes (Q6746357) (← links)
