http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
data-driven algorithms, learning systems, and predictions
IBM Research—Zurich, Rueschlikon, Switzerland.
COMPUTERS / Data Science / Machine Learning.
1 online resource (139 pages) : illustrations.
Atomic-Scale Representation and Statistical Learning of Tensorial Properties / Grisafi, Andrea; Wilkins, David M.; Willatt, Michael J.; Ceriotti, Michele / Prediction of Mohs Hardness with Machine Learning Methods Using Compositional Features / Garnett, Joy C. / High-Dimensional Neural Network Potentials for Atomistic Simulations / Hellström, Matti, Software for Chemistry & Materials BV, De Boelelaan 1083, 1081HV Amsterdam, The Netherlands; Behler, Jörg, Universität Göttingen, Institut für Physikalische Chemie, Theoretische Chemie, Tammannstrasse 6, 37077 Göttingen, Germany / Data-Driven Learning Systems for Chemical Reaction Prediction: An Analysis of Recent Approaches / Schwaller, Philippe, IBM Research – Zurich, Rueschlikon 8803, Switzerland, Department of Chemistry and Biochemistry, University of Berne, Berne 3012, Switzerland; Laino, Teodoro, IBM Research – Zurich, Rueschlikon 8803, Switzerland / Using Machine Learning To Inform Decisions in Drug Discovery: An Industry Perspective / Green, Darren V. S. / Cognitive Materials Discovery and Onset of the 5th Discovery Paradigm / Zubarev, Dmitry Y.; Pitera, Jed W. / Editors’ Biographies /
Edward O. Pyzer-Knapp, editor, Teodoro Laino, editor ; sponsored by the ACS Division of Computers in Chemistry.
Distributed in print by Oxford University Press.
Includes bibliographical references and index.
SCIENCE / Chemistry / Computational & Molecular Modeling