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Results for stat.ME

Publications & Outputs

  1. Concave-Convex PDMP-based sampling

    Sutton, M. & Fearnhead, P., 30/05/2023, (E-pub ahead of print) In: Journal of Computational and Graphical Statistics. 22 p.

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

  2. CoinEM: Tuning-Free Particle-Based Variational Inference for Latent Variable Models

    Sharrock, L., Dodd, D. & Nemeth, C., 24/05/2023.

    Research output: Working paper › Preprint

  3. Learning Rate Free Bayesian Inference in Constrained Domains

    Sharrock, L., Mackey, L. & Nemeth, C., 24/05/2023.

    Research output: Working paper › Preprint

  4. Automatic Locally Stationary Time Series Forecasting with application to predicting U.K. Gross Value Added Time Series under sudden shocks caused by the COVID pandemic

    Killick, R., Knight, M. I., Nason, G. P., Nunes, M. A. & Eckley, I. A., 14/03/2023.

    Research output: Working paper › Preprint

  5. 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

  6. Transport Elliptical Slice Sampling

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

    Research output: Working paper › Preprint

  7. Detecting Abrupt Changes in the Presence of Local Fluctuations and Autocorrelated Noise

    Romano, G., Rigaill, G., Runge, V. & Fearnhead, P., 31/12/2022, In: Journal of the American Statistical Association. 117, 540, p. 2147-2162

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

  8. Automatic Change-Point Detection in Time Series via Deep Learning

    Li, J., Fearnhead, P., Fryzlewicz, P. & Wang, T., 7/11/2022, Arxiv.

    Research output: Working paper › Preprint

  9. Detecting A Single Change-point

    Fearnhead, P. & Fryzlewicz, P., 13/10/2022, Arxiv.

    Research output: Working paper › Preprint

  10. Testing for a Change in Mean After Changepoint Detection

    Jewell, S., Fearnhead, P. & Witten, D., 30/09/2022, In: Journal of the Royal Statistical Society: Series B (Statistical Methodology). 84, 4, p. 1082-1104 23 p.

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

  11. 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

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