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Sebastian Schmon

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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

2020

• S. M. Schmon , G. Deligiannidis , A. Doucet , M. K. Pitt , Large-sample asymptotics of the pseudo-marginal method, Biometrika, Jul. 2020.
  
  @article{Schmon2020b,
    author = {Schmon, Sebastian M and Deligiannidis, George and Doucet, Arnaud and Pitt, Michael K},
    journal = {Biometrika},
    title = {{Large-sample asymptotics of the pseudo-marginal method}},
    year = {2020},
    month = jul,
    doi = {10.1093/biomet/asaa044}
  }
  

• S. Schmon , A. Doucet , G. Deligiannidis , Bernoulli race particle filters, in AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics, 2020.
  

  @conference{schmon2019bernoulli,
    author = {Schmon, S.M. and Doucet, A. and Deligiannidis, G.},
    title = {Bernoulli race particle filters},
    journal = {AISTATS 2019 - 22nd International Conference on Artificial Intelligence and Statistics},
    year = {2020}
  }
  

• S. Schmon , G. Deligiannidis , A. Doucet , M. Pitt , Large sample asymptotics of the pseudo-marginal method, Biometrika, 2020.
  

  @article{schmon2018large,
    title = {Large sample asymptotics of the pseudo-marginal method},
    author = {Schmon, S.M. and Deligiannidis, G. and Doucet, A. and Pitt, M.K.},
    journal = {Biometrika},
    year = {2020}
  }
  

• T. Joy , S. M. Schmon , P. Torr , S. Narayanaswamy , T. Rainforth , Rethinking Semi–Supervised Learning in VAEs, https://arxiv.org/abs/2006.10102, 2020.
  

  @article{Joy2020,
    author = {Joy, Tom and Schmon, Sebastian M and Torr, Philipp and Narayanaswamy, Siddharth and Rainforth, Tom},
    journal = {https://arxiv.org/abs/2006.10102},
    title = {Rethinking Semi–Supervised Learning in VAEs},
    year = {2020}
  }
  

• S. Groha , S. M. Schmon , A. Gusev , Neural ODEs for Multi-state Survival Analysis, https://arxiv.org/abs/2006.04893, 2020.
  

  @article{Groha2020,
    author = {Groha, Stefan and Schmon, Sebastian M and Gusev, Alexander},
    title = {Neural ODEs for Multi-state Survival Analysis},
    journal = {https://arxiv.org/abs/2006.04893},
    year = {2020}
  }
  

• S. M. Schmon , P. W. Cannon , J. Knoblauch , Generalized Posteriors in Approximate Bayesian Computation. 2020.
  

  @misc{schmon2020generalized,
    title = {Generalized Posteriors in Approximate Bayesian Computation},
    author = {Schmon, Sebastian M and Cannon, Patrick W and Knoblauch, Jeremias},
    year = {2020},
    eprint = {2011.08644},
    archiveprefix = {arXiv},
    primaryclass = {stat.ME}
  }
  

2019

• S. M. Schmon , G. Deligiannidis , A. Doucet , Bernoulli Race Particle Filters, AISTATS, 2019.
  

  @article{bernrace,
    author = {Schmon, Sebastian M and Deligiannidis, George and Doucet, Arnaud},
    title = {Bernoulli Race Particle Filters},
    journal = {AISTATS},
    year = {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.
  

  @article{Fitzsimons2019,
    author = {Fitzsimons, Jack K and Schmon, Sebastian M and Roberts, Stephen J},
    journal = {4th Neurips workshop on Bayesian Deep Learning},
    title = {Implicit Priors for Knowledge Sharing in Bayesian Neural Networks},
    year = {2019}
  }