Samuel Wiqvist (Former)
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- 2022
-
Mark
Scalable and flexible inference framework for stochastic dynamic single-cell models
- Contribution to journal › Article
- 2021
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Mark
Sequential Neural Posterior and Likelihood Approximation
(2021)
- Working paper/Preprint › Preprint in preprint archive
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Mark
PEPSDI: Scalable and flexible inference framework for stochastic dynamic single-cell models
(2021)
- Working paper/Preprint › Preprint in preprint archive
-
Mark
Simulation-based Inference : From Approximate Bayesian Computation and Particle Methods to Neural Density Estimation
- Thesis › Doctoral thesis (compilation)
-
Mark
Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms
- Contribution to journal › Article
- 2019
-
Mark
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
(2019)
- Working paper/Preprint › Working paper
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Mark
Partially exchangeable networks and architectures for learning summary statistics in approximate Bayesian computation
(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
- 2018
-
Mark
Accelerating delayed-acceptance Markov chain Monte Carlo algorithms
(2018)
- Working paper/Preprint › Working paper