F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits. - Chiara Leadbeater; Louis Sharrock; Brian Coyle; Marcello Benedetti (Entropy, 2021)

Joint Online Parameter Estimation and Optimal Sensor Placement for the Partially Observed Stochastic Advection-Diffusion Equation. - Louis Sharrock; Nikolas Kantas (SIAM/ASA J. Uncertain. Quantification, 2022)

Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates. - Louis Sharrock; Christopher Nemeth (ICML, 2023)

Learning Rate Free Bayesian Inference in Constrained Domains. - Louis Sharrock; Lester Mackey; Christopher Nemeth (NeurIPS, 2023)

CoinEM: Tuning-Free Particle-Based Variational Inference for Latent Variable Models. - Louis Sharrock; Daniel Dodd; Christopher Nemeth (CoRR, 2023)

Tuning-Free Maximum Likelihood Training of Latent Variable Models via Coin Betting. - Louis Sharrock; Daniel Dodd; Christopher Nemeth (AISTATS, 2024)

Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds. - Daniel Dodd; Louis Sharrock; Christopher Nemeth (ICML, 2024)

Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models. - Louis Sharrock; Jack Simons; Song Liu; Mark Beaumont (ICML, 2024)

Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows. - Alberto Cabezas; Louis Sharrock; Christopher Nemeth (NeurIPS, 2024)