This GitHub repository includes some of the simulation studies and data analysis included in the paper: Maceda, E., Hector, E. C., Lenzi, A., & Reich, B. J. (2024). A variational neural Bayes framework for inference on intractable posterior distributions. arXiv preprint arXiv:2404.10899.
Instructions for running each of the simulation studies and data analysis are provided in their respective directories.
Please email eamaceda@ncsu.edu with any questions or bug-reports.
If you use VaNBayes, please consider citing the relevant manuscript: Maceda, E., Hector, E. C., Lenzi, A., & Reich, B. J. (2024). A variational neural Bayes framework for inference on intractable posterior distributions. arXiv preprint arXiv:2404.10899.
Parker Trostle, Joseph Guinness, Brian J Reich, A Gaussian-process approximation to a spatial SIR process using moment closures and emulators, Biometrics, Volume 80, Issue 3, September 2024, ujae068, https://doi.org/10.1093/biomtc/ujae068
Zakhar Kabluchko, Martin Schlather, Laurens de Haan "Stationary max-stable fields associated to negative definite functions," The Annals of Probability, Ann. Probab. 37(5), 2042-2065, (September 2009)