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Recent advances in machine learning or artificial intelligence for vision and natural language processing that have enabled the development of new technologies such as personal assistants or self-driving cars have brought machine learning and artificial intelligence to the forefront of popular culture. The accumulation of these algorithmic advances along with the increasing availability of large data sets and readily available high performance computing has played an important role in bringing machine learning applications to such a wide range of disciplines. Given the emphasis in the chemical sciences on the relationship between structure and function, whether in biochemistry or in materials chemistry, adoption of machine learning by chemistsderivations where they are important
Published since 1959, this serial presents in-depth reviews of key topics in neuroscience, from molecules to behavior. The serial stays keenly atuned to recent developments through the contributions of first-class experts in the many fields of neuroscience. Neuroscientists as well as clinicians, psychologists, physiologists and pharmacoloists will find this serial an indispensable addition to their library.
First published in 1976. Routledge is an imprint of Taylor & Francis, an informa company.
As the co-authors present 13 of American Prof. of Russian Lee B. Croft's scholarly articles (in English with Russian examples), the articles fascinate as they advance the reader's knowledge of: glossolalia, poetic decipherment and translation, language philosophy and psychology, linguistic iconicity and language universals, an American Nobel-laureate scientist's inspiration, literary pornography, pervasive triplicity, spontaneous human combustion and polylingual alphamagic squares.
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. - Compiles advances of machine learning in quantum chemistry across different areas into a single resource - Provides insights into the underlying concepts of machine learning techniques that are relevant to quantum chemistry - Describes, in detail, the current state-of-the-art machine learning-based methods in quantum chemistry