Louis Sharrock
Senior Research Associate in Statistical Machine Learning
Fry Building
Woodland Road
Bristol, BS8 1UG
About. I am a Senior Research Associate in Statistical Machine Learning working with Prof. Chris Nemeth at Lancaster University, and an Honorary Senior Research Associate at the University of Bristol. I was previously a Data Science Heilbronn Research Fellow at the University of Bristol. I obtained my PhD in the Department of Mathematics at Imperial College London, supervised by Dr. Nikolas Kantas. I hold an MRes in Mathematics and an MSc in Statistics from Imperial College London, and an MA in Mathematics from the University of Cambridge.
Research. My research interests include computational statistics, machine learning, and optimisation, with a particular focus on stochastic gradient Markov Chain Monte Carlo methods and likelihood free inference. My current research focuses on learning-rate free sampling algorithms, score-based methods for simulation based inference, and online inference for interacting particle systems and mean-field equations.
news
May 23, 2024 | We have a new preprint on “Markovian Flow Matching” on the arXiv! Check it out here. |
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May 1, 2024 | Our paper - “Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds” - has also been accepted as a spotlight at ICML 2024! |
May 1, 2024 | Our paper - “Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models” - has been accepted as a spotlight at ICML 2024! |
Jan 19, 2024 | Our paper - “Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting” - has been accepted to AISTATS 2024! |
Oct 20, 2023 | We are organising an exciting workshop at the RSS on Gradient Flows for Sampling, Inference, and Learning. Click here for more details. |
Sep 21, 2023 | Our paper - “Learning Rate Free Sampling in Constrained Domains” - has been accepted to NeurIPS 2023! |
Sep 8, 2023 | In Feb 2024, I will give an invited talk on parameter-free optimisation on the space of probability measures at ISMP 2024. |
Aug 14, 2023 | In Feb 2024, I will give an invited talk on online parameter estimation for interacting particle systems at the SIAM Conference on Uncertainty Quantification. |
May 24, 2023 | We have two new preprints up on arXiv! Check them out here and here. |
May 3, 2023 | Our paper - “Online Parameter Estimation for the McKean-Vlasov Stochastic Differential Equation” - has been accepted to Stochastic Processes and their Applications. |
Apr 24, 2023 | Our paper - “Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates” - has been accepted to ICML 2023! |
Apr 17, 2023 | On 9th June I will give a talk about our recent work on coin sampling in the OxCSML seminar series. |