| 2022 | ||
| 2021 | ||
| Monday 6 Dec | Ardjen | Strong Invariance Principles for Ergodic Markov Processes. [link] |
| Friday 14 Oct | Paul | Estimates, uniformly in time. |
| Thursday 30 Sep | Joris | Akaike, H. (1974). A new look at the statistical model identification. [link] |
| Thursday 1 Jul | Andrea | Nagapetyan, T., Duncan, A. B., Hasenclever, L., Vollmer, S. J., Szpruch, L., & Zygalakis, K. (2017). The True Cost of Stochastic Gradient Langevin Dynamics. [link] |
| Friday 18 Jun | Sebastiano | Roberts, G. O., Rosenthal, J. S., & Tawn, N. G. (2020). Skew Brownian Motion and Complexity of the ALPS Algorithm. [link] |
| Friday 11 Jun | Ardjen | Van Der Vaart, A. W., & Van Zanten, J. H. (2008). Rates of contraction of posterior distributions based on Gaussian process priors. [link] |
| Thursday 20 May | Paul | Garbuno-Inigo, A., Hoffmann, F., Li, W., & Stuart, A. M. (2020). Interacting Langevin diffusions: Gradient structure and ensemble Kalman sampler. [link] |
| Friday 30 April | Joris | Coghi, F., Chetrite, R., & Touchette, H. (2021). Role of current fluctuations in nonreversible samplers. [link] |
| Wednesday 14 Apr | Andrea | Coupling of Euler approximations for PDMC. [link] |
| Friday 26 Mar | Sebastiano | Nishimura, A., Dunson, D., & Lu, J. (2017). Discontinuous Hamiltonian Monte Carlo for discrete parameters and discontinuous likelihoods. [link] |
| Thursday 11 Mar | Ardjen | Chwialkowski, K., Strathmann, H., & Gretton, A. (2016). A kernel test of goodness of fit. [link] |
| Thursday 25 Feb | Paul | N. Ross (2011). Fundamentals of Stein's method, continued. [link] |
| Thursday 11 Feb | Joris | N. Ross (2011). Fundamentals of Stein's method, continued. [link] |
| Friday 29 Jan | Andrea | N. Ross (2011). Fundamentals of Stein's method, continued. [link] |
| Friday 14 Jan | Sebastiano | N. Ross (2011). Fundamentals of Stein's method, continued. [link] |
| 2020 | ||
| Thursday 10 Dec | Ardjen | N. Ross (2011). Fundamentals of Stein's method. [link] |
| Friday 27 Nov | Sjoerd | Spectral analysis for the zigzag process on the torus. |
| Thursday 12 Nov | Paul |
Lu, J., & Wang, L. (2020). On explicit L^2-convergence rate estimate for piecewise deterministic Markov processes. [link] Cao, Y., Lu, J., & Wang, L. (2019). On explicit L^2-convergence rate estimate for underdamped Langevin dynamics. [link] |
| Thursday 29 Oct | Joris | O’Leary, J., Wang, G., & Jacob, P. E. (2020). Maximal couplings of the Metropolis-Hastings algorithm. [link] |
| Thursday 15 Oct | Andrea | Durmus, A., & Moulines, É. (2019). High-dimensional Bayesian inference via the unadjusted Langevin algorithm. Bernoulli, 25(4 A), 2854–2882. [link] |
| Thursday 1 Oct | Sebastiano | Syed, S., Bouchard-Côté, A., Deligiannidis, G., & Doucet, A. (2019). Non-Reversible Parallel Tempering: a Scalable Highly Parallel MCMC Scheme. [link] |
| Thursday 10 Sep | Ardjen | Chapters 1, 2 of Komorowski, T., Landim, C., & Olla, S. (2012). Fluctuations in Markov processes. Springer, Heidelberg. [link] Duncan, A. B., Lelièvre, T., & Pavliotis, G. A. (2015). Variance Reduction using Nonreversible Langevin Samplers. Journal of Statistical Physics. [link] |
| Tuesday 23 June | Paul | Mattingly, J. C., Stuart, A. M., & Tretyakov, M. V. (2010). Convergence of Numerical Time-Averaging and Stationary Measures via Poisson Equations. SIAM Journal on Numerical Analysis, 48(2), 552–577. [link] |
| Tuesday 9 Jun | Joris | Gorham, J., & Mackey, L. (2015). Measuring Sample Quality with Stein’s Method. Advances in Neural Information Processing Systems 28, 226–234. [link] Gorham, J., Duncan, A. B., Vollmer, S. J., & Mackey, L. (2019). Measuring sample quality with diffusions. Ann. Appl. Probab., 29(5), 2884–2928. [link] [notes] |
| Tuesday 26 May | Andrea | Rosenthal, J. S. (2003). Asymptotic variance and convergence rates of nearly-periodic Markov chain Monte Carlo algorithms. Journal of the American Statistical Association, 98(461), 169–177. [link] |
| Tuesday 12 May | Sebastiano | Cotter, S. L., Roberts, G. O., Stuart, A. M., & White, D. (2013). MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster. Statistical Science, 28(3), 424–446. [link] |
| Tuesday 28 Apr | Ardjen | Hobert, J. P., Jones, G. L., Presnell, B., & Rosenthal, J. S. (2002). On the Applicability of Regenerative Simulation in Markov Chain Monte Carlo. Biometrika, 89(4), 731–743. [link] Löcherbach, E., & Loukianova, D. (2008). On Nummelin splitting for continuous time Harris recurrent Markov processes and application to kernel estimation for multi-dimensional diffusions. Stochastic Processes and Their Applications, 118(8), 1301–1321. [link] |
| Tuesday 15 Apr | Paul | Barré, J., Dobson, P., Ottobre, M., & Zatorska, E. (2020). Fast non mean-field networks: uniform in time averaging. [link] |
| Tuesday 31 Mar | Joris | Zig-Zag and BPS for anisotropic targets |
| Tuesday 10 Mar | Andrea | Jacob, P. E., O’Leary, J., & Atchadé, Y. F. (2020). Unbiased Markov chain Monte Carlo with couplings. J. R. Stat. Soc. B, 82(2), 1–32. [link] |
| Tuesday 18 Feb | Sebastiano | Roberts, G. O., Gelman, A., & Gilks, W. R. (1997). Weak convergence and optimal scaling of random walk Metropolis algorithms. The Annals of Applied Probability, 7(1), 110–120. [link] Roberts, G. O., & Rosenthal, J. S. (1998). Optimal scaling of discrete approximations to Langevin diffusions. Journal of the Royal Statistical Society: Series B (Statistical Methodology), 60(1), 255–268. [link] Roberts, G. O., & Rosenthal, J. S. (2001). Optimal scaling for various Metropolis-Hastings algorithms. Statistical Science, 16(4), 351–367. [link] |
| Tuesday 21 Jan | Joris | Guillin, A., & Nectoux, B. (2020). Low lying eigenvalues and convergence to the equilibrium of some Piecewise Deterministic Markov Processes generators in the small temperature regime. [link] |
| 2019 | ||
| Tuesday 17 Dec | Ardjen | Flegal, J. M., & Jones, G. L. (2010). Batch means and spectral variance estimators in Markov chain Monte Carlo. The Annals of Statistics, 38(2), 1034–1070. |
| Friday 29 Nov | Paul | Andrieu, C., Durmus, A., Nüsken, N., & Roussel, J. (2018). Hypocoercivity of Piecewise Deterministic Markov Process-Monte Carlo. ArXiv Preprint ArXiv: 1808.08592. [link] Dolbeault, J., Mouhot, C., & Schmeiser, C. (2015). Hypocoercivity for linear kinetic equations conserving mass. Transactions of the American Mathematical Society, 367(6), 3807–3828. [link] |
| Friday 1 Nov | Andrea | Roberts, G. O., & Rosenthal, J. S. (2007). Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms. Journal of Applied Probability, 44(02), 458–475. [link] |
| Thursday 17 Oct | Sebastiano | Andrieu, C., & Livingstone, S. (2019). Peskun-Tierney ordering for Markov chain and process Monte Carlo: beyond the reversible scenario, 1–38. [link] |
| Thursday 3 Oct | Joris | Meet & Greet |