Deep Learning Dynamical Latencies for the Parameterization of Complex Chemical Kinetics

(2025) CYPHER Workshop on Machine Learning for Complex Flows — Location: Madrid, Spain (6.February.2025)

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Abstract
In this work, the implementation of time-lag autoencoders for chemical kinetics reductions is expanded to complex chemical kinetics (i.e, mechanisms with hundreds of species). A sampling methodology is analyzed for efficient hyperparameter optimization, enabling for a data-efficient methodology.
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Citations

Castellanos, L., & et al. (2025). Deep Learning Dynamical Latencies for the Parameterization of Complex Chemical Kinetics. CYPHER Workshop on Machine Learning for Complex Flows, Madrid, Spain. https://hdl.handle.net/2078.5/267996