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Research

Professor Christopher Nemeth

Professor in Statistics, Research Student

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  1. Forthcoming

    Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting

    Sharrock, L., Dodd, D. & Nemeth, C., 19/01/2024, (Accepted/In press) In: Proceedings of Machine Learning Research.

    Research output: Contribution to Journal/Magazine › Conference article › peer-review

  2. Published

    Transport Elliptical Slice Sampling

    Cabezas, A. & Nemeth, C., 25/04/2023, In: Proceedings of Machine Learning Research. 206, p. 3664-3676 13 p.

    Research output: Contribution to Journal/Magazine › Conference article › peer-review

  3. Published

    Telling the Researcher STOR-i With Data Science: Elsevier data scientists are working with Lancaster University researchers to advance our understanding of researcher behaviors

    Bolt, G., Muncey, H., Lunagomez Coria, S. & Nemeth, C., 2020

    Research output: Exhibits, objects and web-based outputs › Web publication/site

  4. Published

    SwISS: A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy

    Vyner, C., Nemeth, C. & Sherlock, C., 8/08/2022.

    Research output: Working paper › Preprint

  5. Published

    SwISS: A Scalable Markov chain Monte Carlo Divide-and-Conquer Strategy

    Vyner, C., Nemeth, C. & Sherlock, C., 31/12/2023, In: Stat. 12, 1, 11 p., e523.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  6. Published

    Stochastic Gradient MCMC for Nonlinear State Space Models

    Aicher, C., Putcha, S., Nemeth, C., Fearnhead, P. & Fox, E. B., 29/01/2019, In: arXiv.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  7. Forthcoming

    Stochastic Gradient MCMC for Nonlinear State Space Models

    Aicher, C., Putcha, S., Nemeth, C., Fearnhead, P. & Fox, E. B., 8/06/2023, (Accepted/In press) In: Bayesian Analysis.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  8. Published

    Stochastic gradient Markov chain Monte Carlo

    Nemeth, C. & Fearnhead, P., 30/03/2021, In: Journal of the American Statistical Association. 1116, 533, p. 433-450 18 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  9. Published

    Stein Variational Gaussian Processes

    Pinder, T., Nemeth, C. & Leslie, D., 25/09/2020, In: arXiv.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  10. Published

    SGMCMCJax: a lightweight JAX library for stochastic gradient Markov chain Monte Carlo algorithms

    Coullon, J. & Nemeth, C., 18/04/2022, In: Journal of Open Source Software. 7, 72, 2 p., 4113.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  11. Published

    sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo

    Baker, J., Fearnhead, P., Fox, E. B. & Nemeth, C. J., 31/10/2019, In: Journal of Statistical Software. 91, 3, p. 1-27 27 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  12. Published

    Sequential Monte Carlo methods for state and parameter estimation in abruptly changing environments

    Nemeth, C., Fearnhead, P. & Mihaylova, L., 1/03/2014, In: IEEE Transactions on Signal Processing. 62, 5, p. 1245-1255 11 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  13. Published

    Sequential Estimation of Temporally Evolving Latent Space Network Models

    Turnbull, K., Nemeth, C., Nunes, M. & McCormick, T., 31/03/2023, In: Computational Statistics and Data Analysis. 179, 107627.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  14. Published

    Semi-Exact Control Functionals From Sard's Method

    South, L., Karvonen, T., Nemeth, C. J., Girolami, M. & Oates, C. J., 31/01/2020, In: arXiv.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  15. Published

    Semi-Exact Control Functionals From Sard's Method

    South, L., Karvonen, T., Nemeth, C., Girolami, M. & Oates, C. J., 30/06/2022, In: Biometrika. 109, 2, p. 351-367 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  16. E-pub ahead of print

    Seconder of the vote of thanks and contribution to the Discussion of ‘the Discussion Meeting on Probabilistic and statistical aspects of machine learning’

    Nemeth, C., 2/01/2024, (E-pub ahead of print) In: Journal of the Royal Statistical Society: Series B (Statistical Methodology).

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  17. Published

    Robust Bayesian Nonparametric Variable Selection for Linear Regression

    Cabezas, A., Battiston, M. & Nemeth, C., 23/05/2021.

    Research output: Working paper › Preprint

  18. Published

    Pseudo-extended Markov chain Monte Carlo

    Nemeth, C., Lindsten, F., Filippone, M. & Hensman, J., 8/12/2019, p. 1-11. 11 p.

    Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

  19. Forthcoming

    Preferential Subsampling for Stochastic Gradient Langevin Dynamics

    Putcha, S., Nemeth, C. & Fearnhead, P., 23/02/2023, (Accepted/In press) Proceedings of Machine Learning Research, (Artificial Intelligence and Statistics; vol. 206).

    Research output: Working paper › Preprint

  20. Published

    Preferential Subsampling for Stochastic Gradient Langevin Dynamics

    Putcha, S., Nemeth, C. & Fearnhead, P., 27/04/2023, In: Proceedings of Machine Learning Research. 206, p. 8837-8856 20 p.

    Research output: Contribution to Journal/Magazine › Conference article › peer-review

  21. Published

    Particle Metropolis-adjusted Langevin algorithms

    Nemeth, C., Sherlock, C. & Fearnhead, P., 09/2016, In: Biometrika. 103, 3, p. 701-717 17 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  22. Unpublished

    Particle Metropolis adjusted Langevin algorithms for state space models

    Nemeth, C. & Fearnhead, P., 4/02/2014, (Unpublished) In: arxiv.org.

    Research output: Contribution to Journal/Magazine › Journal article

  23. Published

    Particle Learning Methods for State and Parameter Estimation

    Nemeth, C., Fearnhead, P., Mihaylova, L. & Vorley, D., 15/05/2012, Data Fusion & Target Tracking Conference (DF&TT 2012): Algorithms & Applications, 9th IET. 6 p.

    Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review

  24. Published

    Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost

    Nemeth, C., Fearnhead, P. & Mihaylova, L. S., 11/2016, In: Journal of Computational and Graphical Statistics. 25, 4, p. 1138-1157 20 p.

    Research output: Contribution to Journal/Magazine › Journal article › peer-review

  25. Published

    Parameter estimation for state space models using sequential Monte Carlo algorithms

    Nemeth, C., 2014, Lancaster University. 204 p.

    Research output: Thesis › Doctoral Thesis

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