Machine Learning in Chemistry Data-Driven Algorithms, Learning Systems, and Predictions

  • 3h 5m
  • Edward O. Pyzer-Knapp, Teodoro Laino
  • Oxford University Press (US)
  • 2020

Artificial intelligence, and especially its application to chemistry, is an exciting and rapidly expanding area of research. This volume presents groundbreaking work in this field to facilitate researcher engagement and to serve as a solid base from which new researchers can break into this exciting and rapidly transforming field. This interdisciplinary volume will be a valuable tool for those working in cheminformatics, physical chemistry, and computational chemistry.

In this Book

  • Atomic-Scale Representation and Statistical Learning of Tensorial Properties
  • Prediction of Mohs Hardness with Machine Learning Methods Using Compositional Features
  • High-Dimensional Neural Network Potentials for Atomistic Simulations
  • Data-Driven Learning Systems for Chemical Reaction Prediction: An Analysis of Recent Approaches
  • Using Machine Learning to Inform Decisions in Drug Discovery: An Industry Perspective
  • Cognitive Materials Discovery and Onset of the 5th Discovery Paradigm


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