Description
This groundbreaking book examines the intersection of molecular networking, statistical mechanics, and modern artificial intelligence. Authors Caroline Desgranges and Jerome Delhommelle provide readers with essential insights into how machine learning algorithms are revolutionizing our understanding of complex molecular systems.
The text covers fundamental principles of statistical mechanics while demonstrating practical applications of AI and machine learning in molecular research. It addresses advanced computational techniques, neural networks, and data-driven approaches to solving classical problems in molecular science. Ideal for researchers, graduate students, and professionals in chemistry, physics, materials science, and computational biology, this resource equips readers with the tools needed to leverage AI in molecular system analysis and prediction.
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