63 citations · 246 across the 20 of their papers we have counts for
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Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms
Samuel Wiqvist, Andrew Golightly, Ashleigh T. McLean +1
Stochastic differential equation mixed-effects models (SDEMEMs) are flexible hierarchical models that are able to account for random variability inherent in the underlying time-dyn…
Stratified sampling and bootstrapping for approximate Bayesian computation
Umberto Picchini, Richard G. Everitt
Approximate Bayesian computation (ABC) is computationally intensive for complex model simulators. To exploit expensive simulations, data-resampling via bootstrapping can be employe…
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation
Samuel Wiqvist, Pierre-Alexandre Mattei, Umberto Picchini +1
We present a novel family of deep neural architectures, named partially exchangeable networks (PENs) that leverage probabilistic symmetries. By design, PENs are invariant to block-…