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Bounding the equilibrium distribution of Markov population models.

, , , and . Numerical Lin. Alg. with Applic., 18 (6): 931-946 (2011)

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Rule-based modelling and simulation of drug-administration policies., , , and . SpringSim (MSM), page 53-60. SCS/ACM, (2015)Recombinant Service Systems Engineering., , and . Business & Information Systems Engineering, 60 (5): 377-391 (2018)SHAVE: stochastic hybrid analysis of markov population models., , and . HSCC, page 311-312. ACM, (2011)Ambidexterity in Service Innovation Research: A Systematic Literature Review.. Wirtschaftsinformatik, page 751-765. University of Siegen, Germany / AISeL, (2019)Student Performance Prediction and Optimal Course Selection: An MDP Approach., and . SEFM Workshops, volume 10729 of Lecture Notes in Computer Science, page 40-47. Springer, (2017)Understanding Smart Service Systems Transformation - A Socio-Technical Perspective.. ECIS, (2020)Analysis of Markov Jump Processes under Terminal Constraints., , , and . CoRR, (2020)Tracking the Race Between Deep Reinforcement Learning and Imitation Learning., , , and . QEST, volume 12289 of Lecture Notes in Computer Science, page 11-17. Springer, (2020)H(O)TA: estimation of DNA methylation and hydroxylation levels and efficiencies from time course data., , and . Bioinform., 33 (11): 1733-1734 (2017)Workarounds as generative mechanisms for bottom-up process innovation - Insights from a multiple case study., , and . Inf. Syst. J., 33 (5): 1085-1150 (September 2023)