Machine learning in chemistry : the impact of artificial intelligence [E-Book] / edited by Hugh M. Cartwright.
Cartwright, Hugh M., (editor)
Cambridge : Royal Society of Chemistry, 2020
1 online resource (546 pages)
Theoretical and computational chemistry ; 17
Full Text
Table of Contents:
  • 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