Louis Sharrock

According to our database, Louis Sharrock authored at least 10 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Wasserstein Gradient Flows for Batch Bayesian Optimal Experimental Design.

Louis Sharrock

CoRR, March, 2026

2024

Markovian Flow Matching: Accelerating MCMC with Continuous Normalizing Flows.

Alberto Cabezas, Louis Sharrock, Christopher Nemeth

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

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

Louis Sharrock, Jack Simons, Song Liu, Mark Beaumont

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning-Rate-Free Stochastic Optimization over Riemannian Manifolds.

Daniel Dodd, Louis Sharrock, Christopher Nemeth

Proceedings of the Forty-first International Conference on Machine Learning, 2024

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

Louis Sharrock, Daniel Dodd, Christopher Nemeth

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

CoinEM: Tuning-Free Particle-Based Variational Inference for Latent Variable Models.

Louis Sharrock, Daniel Dodd, Christopher Nemeth

CoRR, 2023

Learning Rate Free Bayesian Inference in Constrained Domains.

Louis Sharrock, Lester Mackey, Christopher Nemeth

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates.

Louis Sharrock, Christopher Nemeth

Proceedings of the International Conference on Machine Learning, 2023

2022

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

2021

F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits.

Chiara Leadbeater, Louis Sharrock, Brian Coyle, Marcello Benedetti

Entropy, 2021