4 citations · 4 across the 4 of their papers we have counts for
6 papers
A Distribution-to-Distribution Neural Probabilistic Forecasting Framework for Dynamical Systems
Tianlin Yang, Hailiang Du, Louis Aslett
Probabilistic forecasting provides a principled framework for uncertainty quantification in dynamical systems by representing predictions as probability distributions rather than d…
Ethical considerations of use of hold-out sets in clinical prediction model management
Louis Chislett, Louis JM Aslett, Alisha R Davies +2
Clinical prediction models are statistical or machine learning models used to quantify the risk of a certain health outcome using patient data. These can then inform potential inte…
Model updating after interventions paradoxically introduces bias
James Liley, Samuel R Emerson, Bilal A Mateen +3
Machine learning is increasingly being used to generate prediction models for use in a number of real-world settings, from credit risk assessment to clinical decision support. Rece…
Improved Concentration Bounds for Gaussian Quadratic Forms
Robert E. Gallagher, Louis J. M. Aslett, David Steinsaltz +1
For a wide class of monotonic functions , we develop a Chernoff-style concentration inequality for quadratic forms , where $Z_…
Encrypted accelerated least squares regression
Pedro M. Esperança, Louis J. M. Aslett, Chris C. Holmes
Information that is stored in an encrypted format is, by definition, usually not amenable to statistical analysis or machine learning methods. In this paper we present detailed ana…
Cryptographically secure multiparty evaluation of system reliability
Louis J. M. Aslett
The precise design of a system may be considered a trade secret which should be protected, whilst at the same time component manufacturers are sometimes reluctant to release full t…