Expressive Gaussian mixture models for high-dimensional statistical modelling: simulated data and neural network model files
Introduced by Menary et al. in Learning to discover: expressive Gaussian mixture models for multi-dimensional simulation and parameter inference in the physical sciences
Neural network model files and Madgraph event generator outputs used as inputs to the results presented in the paper "Learning to discover: expressive Gaussian mixture models for multi-dimensional simulation and parameter inference in the physical sciences" arXiv:2108.11481; 2022 Mach. Learn.: Sci. Technol. 3 015021 Code and model files can be found at: https://github.com/darrendavidprice/science-discovery/tree/master/expressive_gaussian_mixture_models
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