Crossref Citations
This article has been cited by the following publications. This list is generated based on data provided by
Crossref.
Zanella, Giacomo
Bédard, Mylène
and
Kendall, Wilfrid S.
2017.
A Dirichlet form approach to MCMC optimal scaling.
Stochastic Processes and their Applications,
Vol. 127,
Issue. 12,
p.
4053.
Beskos, Alexandros
Roberts, Gareth
Thiery, Alexandre
and
Pillai, Natesh
2018.
Asymptotic analysis of the random walk Metropolis algorithm on ridged densities.
The Annals of Applied Probability,
Vol. 28,
Issue. 5,
Ma, Yi-An
Chen, Yuansi
Jin, Chi
Flammarion, Nicolas
and
Jordan, Michael I.
2019.
Sampling can be faster than optimization.
Proceedings of the National Academy of Sciences,
Vol. 116,
Issue. 42,
p.
20881.
Yang, Jun
Roberts, Gareth O.
and
Rosenthal, Jeffrey S.
2020.
Optimal scaling of random-walk metropolis algorithms on general target distributions.
Stochastic Processes and their Applications,
Vol. 130,
Issue. 10,
p.
6094.
Mangoubi, Oren
and
Smith, Aaron
2021.
Mixing of Hamiltonian Monte Carlo on strongly log-concave distributions: Continuous dynamics.
The Annals of Applied Probability,
Vol. 31,
Issue. 5,
Zanella, Giacomo
and
Roberts, Gareth
2021.
Multilevel Linear Models, Gibbs Samplers and Multigrid Decompositions (with Discussion).
Bayesian Analysis,
Vol. 16,
Issue. 4,
Sherlock, Chris
Thiery, Alexandre H.
and
Golightly, Andrew
2021.
Efficiency of delayed-acceptance random walk Metropolis algorithms.
The Annals of Statistics,
Vol. 49,
Issue. 5,
Sherlock, C
and
Thiery, A H
2022.
A discrete bouncy particle sampler.
Biometrika,
Vol. 109,
Issue. 2,
p.
335.
Craiu, Radu V.
Gustafson, Paul
and
Rosenthal, Jeffrey S.
2022.
Reflections on Bayesian inference and Markov chain Monte Carlo.
Canadian Journal of Statistics,
Vol. 50,
Issue. 4,
p.
1213.
Bierkens, Joris
Kamatani, Kengo
and
Roberts, Gareth O.
2022.
High-dimensional scaling limits of piecewise deterministic sampling algorithms.
The Annals of Applied Probability,
Vol. 32,
Issue. 5,
Yang, Jun
and
Rosenthal, Jeffrey S.
2023.
Complexity results for MCMC derived from quantitative bounds.
The Annals of Applied Probability,
Vol. 33,
Issue. 2,