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Understanding the role of autoencoders for stiff dynamical systems using information theory
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Solving the chemical master equation for stochastic biochemical systems: A variational autoencoder approach with effective reactions
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Emulating the interstellar medium chemistry with neural operators
Quantifying the informativity of emission lines to infer physical conditions in giant molecular clouds
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Disentangling CO Chemistry in a Protoplanetary Disk Using Explanatory Machine-learning Techniques
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Neural network-based emulation of interstellar medium models
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A statistical and machine learning approach to the study of astrochemistry