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2021
Mark Sequential Neural Posterior and Likelihood Approximation
Wiqvist, Samuel ^LU ; Picchini, Umberto ^LU and Frellsen, Jes (2021)
- Working paper/Preprint › Preprint in preprint archive
Mark Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms
Wiqvist, Samuel ^LU ; Golightly, Andrew ; McLean, Ashleigh T. and Picchini, Umberto ^LU (2021) In Computational Statistics and Data Analysis 157.
- Contribution to journal › Article
2019
Mark Likelihood-free stochastic approximation EM for inference in complex models
Picchini, Umberto ^LU (2019) In Communications in Statistics: Simulation and Computation 48(3). p.861-881
- Contribution to journal › Article
Mark Partially exchangeable networks and architectures for learning summary statistics in approximate Bayesian computation
Wiqvist, Samuel ^LU ; Mattei, Pierre Alexandre ; Picchini, Umberto ^LU and Frellsen, Jes (2019) 36th International Conference on Machine Learning, ICML 2019 In 36th International Conference on Machine Learning, ICML 2019 2019-June. p.11795-11804
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
Mark Bayesian inference for stochastic differential equation mixed effects models of a tumour xenography study
Picchini, Umberto ^LU and Forman, Julie Lyng (2019) In Journal of the Royal Statistical Society. Series C: Applied Statistics 68(4). p.887-913
- Contribution to journal › Article
2018
Mark Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
Wiqvist, Samuel ^LU ; Picchini, Umberto ^LU and Forman, Julie Lyng (2018)
- Working paper/Preprint › Working paper
Mark Coupling stochastic EM and approximate Bayesian computation for parameter inference in state-space models
Picchini, Umberto ^LU and Samson, Adeline (2018) In Computational Statistics 33(1). p.179-212
- Contribution to journal › Article
2017
Mark Approximate maximum likelihood estimation using data-cloning ABC
Picchini, Umberto ^LU and Anderson, Rachele ^LU (2017) In Computational Statistics & Data Analysis 105. p.166-183
- Contribution to journal › Article
2016
Mark Accelerating inference for diffusions observed with measurement error and large sample sizes using approximate Bayesian computation
Picchini, Umberto ^LU and Forman, Julie Lyng (2016) In Journal of Statistical Computation and Simulation 86(1). p.195-213
- Contribution to journal › Article
2014
Mark Inference for SDE models via Approximate Bayesian Computation
Picchini, Umberto ^LU (2014) In Journal of Computational and Graphical Statistics 23(4). p.1080-1100
- Contribution to journal › Article

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