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Results for stat.ML

Publications & Outputs

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

    Li, J., Fearnhead, P., Fryzlewicz, P. & Wang, T., 2/10/2023, (Accepted/In press) In: Journal of the Royal Statistical Society: Series B (Statistical Methodology).

    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. 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

  5. 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

  6. Reversible Jump PDMP Samplers for Variable Selection

    Chevallier, A., Fearnhead, P. & Sutton, M., 11/07/2022, (E-pub ahead of print) In: Journal of the American Statistical Association.

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

  7. Gaussian Processes on Hypergraphs

    Pinder, T., Turnbull, K., Nemeth, C. & Leslie, D., 3/06/2021.

    Research output: Working paper › Preprint

  8. Efficient and Generalizable Tuning Strategies for Stochastic Gradient MCMC

    Coullon, J., South, L. & Nemeth, C., 27/05/2021, Arxiv.

    Research output: Working paper › Preprint

  9. Dynamic Slate Recommendation with Gated Recurrent Units and Thompson Sampling

    Eide, S., Leslie, D. S. & Frigessi, A., 30/04/2021, In: arxiv.org.

    Research output: Contribution to Journal/Magazine › Journal article

  10. 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

  11. MUMBO: MUlti-task Max-value Bayesian Optimization

    Moss, H. B., Leslie, D. S. & Rayson, P., 14/09/2020, achine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2020, Proceedings. Springer, p. 447-462 16 p.

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

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