Score Matched Neural Exponential Families for Likelihood-Free Inference

• Published in: arXiv.org
• Main Authors: Pacchiardi, Lorenzo, Dutta, Ritabrata
• Format: Paper
• Language: English
• Published: Ithaca Cornell University Library, arXiv.org 31.01.2022
• Subjects: Approximation; Bayesian analysis; Mathematical models; Meteorology; Neural networks; Parameters; Simulation; Statistical inference; Statistical methods

Bayesian Likelihood-Free Inference (LFI) approaches allow to obtain posterior distributions for stochastic models with intractable likelihood, by relying on model simulations. In Approximate Bayesian Computation (ABC), a popular LFI method, summary statistics are used to reduce data dimensionality....