Niall Jeffrey

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 8

Top Topics

Conditional Probabilities

Machine Learning

Parameter Space

Top Venues

Mach. Learn. Sci. Technol.

Astron. Comput.

Publications

Niall Jeffrey, Benjamin D. Wandelt
Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison. Mach. Learn. Sci. Technol. 5 (1) (2024)
Pablo Lemos, Niall Jeffrey, Miles D. Cranmer, Shirley Ho, Peter W. Battaglia
Rediscovering orbital mechanics with machine learning. Mach. Learn. Sci. Technol. 4 (4) (2023)
Niall Jeffrey, Benjamin D. Wandelt
Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparison. CoRR (2023)
Pablo Lemos, Niall Jeffrey, Miles D. Cranmer, Shirley Ho, Peter W. Battaglia
Rediscovering orbital mechanics with machine learning. CoRR (2022)
Benjamin Remy, Francois Lanusse, Niall Jeffrey, Jia Liu, Jean-Luc Starck, Ken Osato, Tim Schrabback
Probabilistic Mass Mapping with Neural Score Estimation. CoRR (2022)
Niall Jeffrey, Benjamin D. Wandelt
Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks. CoRR (2020)
Niall Jeffrey, Alan Heavens, P. D. Fortio
Fast sampling from Wiener posteriors for image data with dataflow engines. Astron. Comput. 25 (2018)
Konstantinos E. Themelis, Francois Lanusse, Niall Jeffrey, Austin Peel, Jean-Luc Starck, Filipe B. Abdalla
Modelling Data with both Sparsity and a Gaussian Random Field: Application to Dark Matter Mass Mapping in Cosmology. EUSIPCO (2018)