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Research

Dr Louis Sharrock

Formerly at Lancaster University

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  1. 2024
  2. Forthcoming

    Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows

    Cabezas Gonzalez, A., Sharrock, L. & Nemeth, C., 25/09/2024, (Accepted/In press) In: Advances in Neural Information Processing Systems.

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

  3. Published

    Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models

    Sharrock, L., Simons, J., Liu, S. & Beaumont, M., 29/07/2024, In: Proceedings of Machine Learning Research. 235, p. 44565-44602 38 p.

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

  4. Published

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

    Sharrock, L., Dodd, D. & Nemeth, C., 19/07/2024, In: Proceedings of Machine Learning Research. 238, p. 1810-1818 9 p.

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

  5. Forthcoming

    Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds

    Dodd, D., Sharrock, L. & Nemeth, C., 1/05/2024, (Accepted/In press) In: Proceedings of Machine Learning Research.

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

  6. 2023
  7. Published

    Learning Rate Free Sampling in Constrained Domains

    Sharrock, L., Mackey, L. & Nemeth, C., 12/12/2023, In: Advances in Neural Information Processing Systems. 36

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

  8. Forthcoming

    Learning Rate Free Bayesian Inference in Constrained Domains

    Sharrock, L., Mackey, L. & Nemeth, C., 21/09/2023, (Accepted/In press) In: Advances in Neural Information Processing Systems. 37

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

  9. Published

    Online parameter estimation for the McKean–Vlasov stochastic differential equation

    Sharrock, L., Kantas, N., Parpas, P. & Pavliotis, G. A., 31/08/2023, In: Stochastic Processes and their Applications. 162, p. 481-546 66 p.

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

  10. Published

    Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates

    Sharrock, L. & Nemeth, C., 23/07/2023, In: Proceedings of Machine Learning Research. 202, p. 30850-30882 33 p.

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

  11. Published

    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

  12. Published

    Learning Rate Free Bayesian Inference in Constrained Domains

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

    Research output: Working paper › Preprint

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