Simulation-based Inference: From Approximate Bayesian Computation and Particle Methods to Neural Density Estimation

Samuel Wiqvist

Forskningsoutput: Avhandling › Doktorsavhandling (sammanläggning)

947 Nedladdningar (Pure)

2021
Sequential Neural Posterior and Likelihood Approximation
Wiqvist, S., Picchini, U. & Frellsen, J., 2021 juni 5, arXiv.org, 28 s.
Forskningsoutput: Working paper/Preprint › Preprint (i preprint-arkiv)
Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms
Wiqvist, S., Golightly, A., McLean, A. T. & Picchini, U., 2021, I: Computational Statistics and Data Analysis. 157, 107151.
Forskningsoutput: Tidskriftsbidrag › Artikel i vetenskaplig tidskrift › Peer review

Öppen tillgång
2019
Partially exchangeable networks and architectures for learning summary statistics in approximate Bayesian computation
Wiqvist, S., Mattei, P. A., Picchini, U. & Frellsen, J., 2019, 36th International Conference on Machine Learning, ICML 2019. International Machine Learning Society (IMLS), s. 11795-11804 10 s. (36th International Conference on Machine Learning, ICML 2019; vol. 2019-June).
Forskningsoutput: Kapitel i bok/rapport/Conference proceeding › Konferenspaper i proceeding › Peer review
2018
Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
Wiqvist, S., Picchini, U. & Forman, J. L., 2018, (Unpublished) 55 s.
Forskningsoutput: Working paper/Preprint › Working paper

Forskningsoutput