Quantum chemistry is simulating atomistic systems according to the
laws of quantum mechanics, and such simulations are essential for
our understanding of the world and for technological progress.
Machine learning revolutionizes quantum chemistry by increasing
simulation speed and accuracy and obtaining new insights. However,
for nonspecialists, learning about this vast field is a formidable
challenge. Quantum Chemistry in the Age of Machine Learning covers
this exciting field in detail, ranging from basic concepts to
comprehensive methodological details to providing detailed codes
and hands-on tutorials. Such an approach helps readers get a quick
overview of existing techniques and provides an opportunity to
learn the intricacies and inner workings of state-of-the-art
methods. The book describes the underlying concepts of machine
learning and quantum chemistry, machine learning potentials and
learning of other quantum chemical properties, machine
learning-improved quantum chemical methods, analysis of Big Data
from simulations, and materials design with machine learning.
Drawing on the expertise of a team of specialist contributors, this
book serves as a valuable guide for both aspiring beginners and
specialists in this exciting field.
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