Towards data-conditional simulation for ABC inference in stochastic differential equations
Preprint, 2023
sequential Monte Carlo
approximate Bayesian computation
smoothing.
synthetic likelihood
invariant neural networks
stochastic differential equations
Author
Petar Jovanovski
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Andrew Golightly
Durham University
Umberto Picchini
Chalmers, Mathematical Sciences, Applied Mathematics and Statistics
Deep learning and likelihood-free Bayesian inference for stochastic modelling
Chalmers AI Research Centre (CHAIR), 2020-01-01 -- 2024-12-31.
Swedish Research Council (VR) (2019-03924), 2020-01-01 -- 2023-12-31.
Statistical Inference and Stochastic Modelling of Protein Folding
Swedish Research Council (VR) (2013-5167), 2014-01-01 -- 2019-12-31.
Subject Categories
Computational Mathematics
Probability Theory and Statistics