Machine Learning in Chemistry

Computers as Scientists;

How Do Machines Learn?;

MedChemInformatics: An Introduction to Machine Learning for Drug Discovery;

Machine Learning for Nonadiabatic Molecular Dynamics;

Machine Learning in Science - A Role for Mechanical Sympathy?;

A Prediction of Future States: AI-powered Chemical Innovation for Defense Applications;

Machine Learning for Chemical Synthesis;

Constraining Chemical Networks in Astrochemistry;

Machine Learning at the (Nano)materials-biology Interface;

Machine Learning Techniques Applied to a Complex Polymerization Process;

Machine Learning and Scoring Functions (SFs) for Molecular Drug Discovery: Prediction and Characterisation of Druggable Drugs and Targets;

Artificial Intelligence Applied to the Prediction of Organic Materials;

A New Era of Inorganic Materials Discovery Powered by Data Science;

Machine Learning Applications in Chemical Engineering;

Representation Learning in Chemistry;

Demystifying Artificial Neural Networks as Generators of New Chemical Knowledge: Antimalarial Drug Discovery as a Case Study;

Machine Learning for Core-loss Spectrum;

Autonomous Science: Big Data Tools for Small Data Problems in Chemistry;

Machine Learning for Heterogeneous Catalysis: Global Neural Network Potential from Construction to Applications;

A Few Guiding Principles for Practical Applications of Machine Learning to Chemistry and Materials