Automated deep abstractions for stochastic chemical reaction networks-Reference-Cited by-同舟云学术

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Automated deep abstractions for stochastic chemical reaction networks

Published:2021-12 Issue: Volume:281 Page:104788
ISSN:0890-5401
Container-title:Information and Computation
language:en
Short-container-title:Information and Computation

Author:

Repin Denis,Petrov Tatjana

Publisher

Elsevier BV

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems,Theoretical Computer Science

Reference33 articles.

1. Exact stochastic simulation of coupled chemical reactions;Gillespie;J. Phys. Chem.,1977

2. Noise-induced mixing and multimodality in reaction networks;Plesa;Eur. J. Appl. Math.,2019

3. Deep abstractions of chemical reaction networks;Bortolussi,2018

4. DARTS: differentiable architecture search;Liu,2019

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Efficient and scalable prediction of stochastic reaction–diffusion processes using graph neural networks;Mathematical Biosciences;2024-09

2. Data-Driven Inference of Chemical Reaction Networks via Graph-Based Variational Autoencoders;Quantitative Evaluation of Systems;2023

3. Approximate Constrained Lumping of Polynomial Differential Equations;Computational Methods in Systems Biology;2023

4. Approximating solutions of the Chemical Master equation using neural networks;iScience;2022-09

5. Approximating Solutions of the Chemical Master Equation using Neural Networks;2022-04-27

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