Abstraction of Markov population dynamics via generative adversarial nets

DOI10.1007/978-3-030-85633-5_2zbMath1491.92090arXiv2106.12981OpenAlexW3202931079MaRDI QIDQ2142099

Francesca Cairoli, Luca Bortolussi, Ginevra Carbone

Publication date: 25 May 2022

Full work available at URL: https://arxiv.org/abs/2106.12981

Mathematics Subject Classification ID

Epidemiology (92D30) Population dynamics (general) (92D25) Biochemistry, molecular biology (92C40) Systems biology, networks (92C42) Applications of continuous-time Markov processes on discrete state spaces (60J28)

Related Items (3)

Generative abstraction of Markov population processes ⋮ Approximate constrained lumping of polynomial differential equations ⋮ Abstraction-based segmental simulation of chemical reaction networks

Uses Software

• PyTorch
• StochPy
• Wasserstein GAN
• PRMLT

Cites Work

• Deep abstractions of chemical reaction networks
• Automated deep abstractions for stochastic chemical reaction networks
• Statistical probabilistic model checking with a focus on time-bounded properties
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