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eess.SY2019★ 5 cited
Geometric fluid approximation for general continuous-time Markov chains
Michalis Michaelides, Jane Hillston, Guido Sanguinetti
Fluid approximations have seen great success in approximating the macro-scale behaviour of Markov systems with a large number of discrete states. However, these methods rely on the…
eess.SY2016★ 2 cited
Property-driven State-Space Coarsening for Continuous Time Markov Chains
Michalis Michaelides, Dimitrios Milios, Jane Hillston +1
Dynamical systems with large state-spaces are often expensive to thoroughly explore experimentally. Coarse-graining methods aim to define simpler systems which are more amenable to…