Sebastian Schmon

Sebastian Schmon

Probabilistic inference, Computational Statistics, Markov chain Monte Carlo, High-Dimensional Statistics

I am a DPhil student at the Department of Statistics. My research interest are Bayesian Statistics and stochastic simulation techniques, in particular, the pseudo-marginal Metropolis-Hastings algorithm for intractable distributions.

My supervisors are Arnaud Doucet and George Deligiannidis.

Publications

2019

  • J. K. Fitzsimons , S. M. Schmon , S. J. Roberts , Implicit Priors for Knowledge Sharing in Bayesian Neural Networks, 4th Neurips workshop on Bayesian Deep Learning, 2019.
  • S. M. Schmon , G. Deligiannidis , A. Doucet , Bernoulli Race Particle Filters, AISTATS, 2019.

2018

  • S. M. Schmon , G. Deligiannidis , A. Doucet , M. K. Pitt , Large Sample Asymptotics of the Pseudo-Marginal Method, arXiv preprint arXiv:1806.10060, 2018.
  • S. M. Schmon , G. Deligiannidis , A. Doucet , M. K. Pitt , Large Sample Asymptotics of the Pseudo-Marginal Algorithm, https://arxiv.org/abs/1806.10060, 2018.

2016

  • M. GroƟ , U. Rendtel , T. Schmid , S. M. Schmon , N. Tzavidis , Estimating the density of ethnic minorities and aged people in Berlin: multivariate kernel density estimation applied to sensitive georeferenced administrative data protected via measurement error, Journal of the Royal Statistical Society: Series A (Statistics in Society), 2016.