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An Introduction to Machine Learning in Molecular Sciences
Graph Neural Networks for Molecules
Voxelized representations of atomic systems for machine learning applications
Development of exchange-correlation functionals assisted by machine learning
Machine-Learning for Static and Dynamic Electronic Structure Theory
Data Quality, Data Sampling and Data Fitting: A Tutorial Guide for Constructing Full-dimensional Accurate Potential Energy Surfaces (PESs) of Molecules and Reactions
Machine Learning Applications in Chemical Kinetics and Thermochemistry
Synthesize in A Smart Way: A Brief Introduction to Intelligence and Automation in Organic Synthesis
Machine Learning for Protein Engineering.
Graph Neural Networks for Molecules
Voxelized representations of atomic systems for machine learning applications
Development of exchange-correlation functionals assisted by machine learning
Machine-Learning for Static and Dynamic Electronic Structure Theory
Data Quality, Data Sampling and Data Fitting: A Tutorial Guide for Constructing Full-dimensional Accurate Potential Energy Surfaces (PESs) of Molecules and Reactions
Machine Learning Applications in Chemical Kinetics and Thermochemistry
Synthesize in A Smart Way: A Brief Introduction to Intelligence and Automation in Organic Synthesis
Machine Learning for Protein Engineering.