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The Bouncy Particle Sampler is a Markov chain Monte Carlo method based on a nonreversible piecewise deterministic Markov process.
Hypocoercive relaxation to equilibrium for some kinetic models
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An Efron-Stein inequality for nonsymmetric statistics
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Hybrid Monte Carlo
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Markov models and optimization , volume 49 of Monographs on Statistics and Applied Probability
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Weak convergence and optimal scaling of random walk Metropolis algorithms
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Optimal scaling of discrete approximations to Langevin diffusions
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Ordinary Differential Equations with Applications , volume 34
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Lectures on logarithmic Sobolev inequalities
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Slice sampling
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Hypoelliptic estimates and spectral theory for Fokker-Planck operators and Witten Laplacians , volume 1862 of Lecture Notes in Mathematics
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Weak convergence of Metropolis algorithms for non-iid target distributions
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Stability and ergodicity of piecewise deterministic Markov processes
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Markov Processes: Characterization and Convergence , volume 282
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Introduction to Hamiltonian Dynamical Systems and the N N -body Problem , volume 90 of Applied Mathematical Sciences
K.R. Meyer, G.R. Hall, and D. Offin · 2009
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Ricci curvature of Markov chains on metric spaces
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Asymptotic analysis for the generalized Langevin equation
M. Ottobre and G.A. Pavliotis · 2011
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Nonasymptotic mixing of the MALA algorithm
N. Bou-Rabee and M. Hairer · 2012
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Geometric ergodicity and the spectral gap of non-reversible Markov chains
I. Kontoyiannis and S.P. Meyn · 2012
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Nonasymptotic convergence analysis for the unadjusted Langevin algorithm
A. Durmus and E. Moulines · 2017
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Long-time behaviour of generalised Zig-Zag process
N. Fétique · 2017
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Rapid mixing of Hamiltonian Monte Carlo on strongly log-concave distributions
O. Mangoubi and A. Smith · 2017
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Stochastic bouncy particle sampler
A. Pakman, D. Gilboa, D. Carlson, and L. Paninski · 2017
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Piecewise deterministic Markov chain Monte Carlo
P. Vanetti, A. Bouchard-Côté, G. Deligiannidis, and A. Doucet · 2017
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Diffusion limits of the random walk metropolis algorithm in high dimensions
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Jump control of probability densities with applications to autonomous vehicle motion
A.R. Mesquita and J.P. Hespanha · 2012
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Rejection-free Monte Carlo sampling for general potentials
E.A.J.F. Peters and G. de With · 2012
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Optimal tuning of the hybrid Monte Carlo algorithm
A. Beskos, N. Pillai, G. Roberts, J.M. Sanz-Serna, and A. Stuart · 2013
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Lévy matters. III , volume 2099 of Lecture Notes in Mathematics
Björn Böttcher, René Schilling, and Jian Wang · 2013
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Spectral gaps for a Metropolis-Hastings algorithm in infinite dimensions
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C. Wu and C.P. Robert · 2017
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Hypocoercivity of piecewise deterministic Markov Process-Monte Carlo
C. Andrieu, A. Durmus, N. Nüsken, and J. Roussel · 2018
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Regularity and stability for the semigroup of jump diffusions with state-dependent intensity
V. Bally, D. Goreac, and V. Rabiet · 2018
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The Bouncy Particle Sampler: A non-reversible rejection-free Markov chain Monte Carlo method
A. Bouchard-Côté, S. J. Vollmer, and A. Doucet · 2018
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Underdamped langevin MCMC: A non-asymptotic analysis
X. Cheng, N. S Chatterji, P. L. Bartlett, and M. I. Jordan · 2018
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Piecewise deterministic Markov processes and their invariant measure
A. Durmus, A. Guillin, and P. Monmarché · 2018
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Spectral methods for Langevin dynamics and associated error estimates
J. Roussel and G. Stoltz · 2018
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Hierarchical models and tuning of random walk metropolis algorithms
M. Bédard · 2019
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Spectral analysis of the zigzag process
J. Bierkens and S. M. V. Lunel · 2019
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Exponential ergodicity of the Bouncy Particle Sampler
G. Deligiannidis, A. Bouchard-Côté, and A. Doucet · 2019
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Log-concave sampling: Metropolis-Hastings algorithms are fast
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Cores for piecewise deterministic Markov processes
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Coupling and convergence for Hamiltonian Monte Carlo
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Geometric ergodicity of the Bouncy Particle Sampler
A. Durmus, A. Guillin, and P. Monmarché · 2020
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On explicit L 2 L^{2} -convergence rate estimate for piecewise deterministic Markov processes
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Efficient MCMC sampling with dimension-free convergence rate using ADMM-type splitting
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Optimal scaling of random-walk Metropolis algorithms on general target distributions
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