Projects per year
Abstract
Likelihoodfree inference methods typically make use of a distance between simulated and real data. A common example is the maximum mean discrepancy (MMD), which has previously been used for approximate Bayesian computation, minimum distance estimation, generalised Bayesian inference, and within the nonparametric learning framework. The MMD is commonly estimated at a rootm rate, where m is the number of simulated samples. This can lead to significant computational challenges since a large m is required to obtain an accurate estimate, which is crucial for parameter estimation. In this paper, we propose a novel estimator for the MMD with significantly improved sample complexity. The estimator is particularly well suited for computationally expensive smooth simulators with low to middimensional inputs. This claim is supported through both theoretical results and an extensive simulation study on benchmark simulators.
Original language  English 

Title of host publication  Proceedings of the 40th International Conference on Machine Learning 
Publisher  Journal of Machine Learning Research 
Pages  22892312 
Number of pages  24 
Publication status  Published  Jul 2023 
Event  International Conference on Machine Learning  Duration: 23 Jul 2023 → 29 Jul 2023 
Conference
Conference  International Conference on Machine Learning 

Period  23/07/23 → 29/07/23 
Fingerprint
Dive into the research topics of 'Optimallyweighted Estimators of the Maximum Mean Discrepancy for LikelihoodFree Inference'. Together they form a unique fingerprint.Projects
 2 Active

Turing AI Fellowship: HumanAI Research Teams  Steering AI in Experimental Design and DecisionMaking
Kaski, S., Bristow, R., Cai, P., Jay, C. & Peek, N.
1/10/21 → 30/09/26
Project: Research

MCAIF: Centre for AI Fundamentals
Kaski, S., Pan, W., Alvarez, M., Mu, T., Sun, M., Mukherjee, A., Sonee, A., Leroy, A., Lee, J., Wang, J., Parakkal Unni, M., Sloman, S., Menary, S., Quilter, T., Hosseinzadeh, A., Mousa, A., Das, A., Glover, E., DURSUN, F., Zhu, H., Abdi, H., Dandago, K., Piriyajitakonkij, M., Rachman, R., Shi, X., Keany, T., Liu, X., Jiang, Y., Wan, Z., Evans, I., Harrison, M. & Harper, A.
1/10/21 → 30/09/26
Project: Research