10 citations · 11 across the 3 of their papers we have counts for
3 papers
stat.ML2019★ 10 cited
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
Geoffrey Roeder, Paul K. Grant, Andrew Phillips +2
We introduce a flexible, scalable Bayesian inference framework for nonlinear dynamical systems characterised by distinct and hierarchical variability at the individual, group, and…
cs.PL2010★ 1 cited
Stochastic Simulation of Process Calculi for Biology
Andrew Phillips, Matthew Lakin, Loïc Paulevé
Biological systems typically involve large numbers of components with complex, highly parallel interactions and intrinsic stochasticity. To model this complexity, numerous programm…
q-bio.MN2007
Compositionality, stochasticity and cooperativity in dynamic models of gene regulation
R. Blossey, L. Cardelli, A. Phillips
We present an approach for constructing dynamic models for the simulation of gene regulatory networks from simple computational elements. Each element is called a ``gene gate'' and…