Publications

Papers

• Sharrock, L., Nemeth, C. (2023). “Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates.” arXiv: 2301.11294.

• Sharrock, L., Simons, J., Liu, S., and Beaumont, N. (2022). “Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models.” arXiv: 2210.04872.

• Sharrock, L. (2022). “Two-Timescale Stochastic Approximation for Bilevel Optimisation Problems in Continuous-Time Models.” Proceedings of the 39th International Conference on Machine Learning (ICML 2022) Workshop on Continuous-Time Methods for Machine Learning. arXiv: 2206.06995.

• Sharrock, L. and Kantas, N. (2022). “Two Timescale Stochastic Gradient Descent in Continuous Time with Applications to Joint Online Parameter Estimation and Optimal Sensor Placement.” To appear in Bernoulli. arXiv: 2007.15998.

• Sharrock, L. and Kantas, N. (2022). “Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation.” SIAM / ASA Journal on Uncertainity Quantification, 10, 55-95. https://doi.org/10.1137/20M1375073.

• Sharrock, L., Kantas, N., Pavliotis, G., and Panos, P. (2022). “Parameter Estimation for the McKean-Vlasov Stochastic Differential Equation.” In revision for Stochastic Processes and their Applications. arXiv: 2106.13751.

• Leadbeater, C.*, Sharrock, L.*, Coyle, B., Benedetti, M. (2021). “F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits.” Entropy, 23, 1281. https://doi.org/10.3390/e23101281.