Pages that link to "Item:Q144289"
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The following pages link to The Zig-Zag Process and Super-Efficient Sampling for Bayesian Analysis of Big Data (Q144289):
Displaying 33 items.
- Strong convergence to two-dimensional alternating Brownian motion processes (Q5090308) (← links)
- Kinetic walks for sampling (Q5114800) (← links)
- Transport Map Accelerated Adaptive Importance Sampling, and Application to Inverse Problems Arising from Multiscale Stochastic Reaction Networks (Q5139357) (← links)
- (Q5214185) (← links)
- Constructing Sampling Schemes via Coupling: Markov Semigroups and Optimal Transport (Q5228360) (← links)
- Limit theorems for the zig-zag process (Q5233190) (← links)
- Generalizing Parallel Replica Dynamics: Trajectory Fragments, Asynchronous Computing, and PDMPs (Q5237173) (← links)
- Stochastic Gradient Markov Chain Monte Carlo (Q5857155) (← links)
- A note on the polynomial ergodicity of the one-dimensional Zig-Zag process (Q5868538) (← links)
- Mini-Batch Metropolis–Hastings With Reversible SGLD Proposal (Q5881093) (← links)
- Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains (Q5885120) (← links)
- Birth–death dynamics for sampling: global convergence, approximations and their asymptotics (Q6050829) (← links)
- Infinite dimensional piecewise deterministic Markov processes (Q6056575) (← links)
- A Benchmark for the Bayesian Inversion of Coefficients in Partial Differential Equations (Q6071826) (← links)
- Non-reversible guided Metropolis kernel (Q6116753) (← links)
- Adaptive Importance Sampling Based on Fault Tree Analysis for Piecewise Deterministic Markov Process (Q6131422) (← links)
- Divide-and-conquer Metropolis-Hastings samplers with matched samples (Q6138717) (← links)
- Speed up Zig-Zag (Q6138921) (← links)
- Polynomial convergence rates of piecewise deterministic Markov processes (Q6164832) (← links)
- Convergence of unadjusted Hamiltonian Monte Carlo for mean-field models (Q6165984) (← links)
- Reversible Jump PDMP Samplers for Variable Selection (Q6185587) (← links)
- Randomized time Riemannian manifold Hamiltonian Monte Carlo (Q6190671) (← links)
- Strong invariance principles for ergodic Markov processes (Q6200877) (← links)
- Computing Bayes: from then `til now (Q6540226) (← links)
- Sampling algorithms in statistical physics: a guide for statistics and machine learning (Q6540237) (← links)
- A langevinized ensemble Kalman filter for large-scale dynamic learning (Q6554553) (← links)
- Sampling constrained continuous probability distributions: a review (Q6602026) (← links)
- Speeding up the zig-zag process (Q6616210) (← links)
- Super-efficient exact Hamiltonian Monte Carlo for the von Mises distribution (Q6620451) (← links)
- Bayesian Inference in Common Microeconometric Models With Massive Datasets by Double Marginalized Subsampling (Q6620968) (← links)
- Sampling using adaptive regenerative processes (Q6632616) (← links)
- Posterior computation with the Gibbs zig-zag sampler (Q6650959) (← links)
- Contraction rate estimates of stochastic gradient kinetic Langevin integrators (Q6667313) (← links)
