Applying Machine Learning Techniques to Predict the Properties of Energetic Materials
Applying Machine Learning Techniques to Predict the Properties of Energetic Materials is a scholarly work, published in 2018 in ''ChemRxiv''. The main subjects of the publication include algorithm, convergence, artificial intelligence, kernel, computer science, explosive velocity, detonation, machine learning, explosive chemicals, noncovalent bonding, energetic material, and drug design. The authors present a comprehensive comparison of machine learning models and several molecular featurization methods - sum over bonds, custom descriptors, Coulomb matrices, bag of bonds, and fingerprints.