Data from: Learning coagulation processes with combinatorially-invariant neural networks



This dataset contains all the necessary information to recreate the study presented in the paper entitled "Learning coagulation processes with combinatorially-invariant neural networks". This consists of (1) the aggregated output files used for machine learning, (2) the machine learning codes used to learn the presented models, (3) the PartMC model source code that was used to generate the simulation data and (4) the Python scripts used construct the scenario library for training and testing simulations. This data was used to investigate a method (combinatorally-invariant neural network) for learning the aerosol process of coagulation. This data may be useful for application of other methods.
Date made availableOct 4 2021
PublisherUniversity of Illinois Urbana-Champaign


  • Coagulation
  • Machine learning
  • Atmospheric chemistry
  • Particle-resolved modeling
  • Atmospheric Science

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