Machine Learning in Molecular Sciences

Chapter 2 Graph Neural Networks for Molecules

Chapter 3 Voxelized Representations of Atomic Systems for Machine Learning Applications

Chapter 4 Development of Exchange-Correlation Functionals Assisted by Machine Learning

Chapter 5 Machine-Learning for Static and Dynamic Electronic Structure Theory

Chapter 6 Data Quality, Data Sampling and Data Fitting: A Tutorial Guide for Constructing Full-Dimensional Accurate Potential Energy Surfaces (PESs) of Molecules and Reactions

Chapter 7 Machine Learning Applications in Chemical Kinetics and Thermochemistry

Chapter 8 Synthesize in a Smart Way: A Brief Introduction to Intelligence and Automation in Organic Synthesis

Chapter 9 Machine Learning for Protein Engineering