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And you can learn the concepts of deep learning through the words of physics. In fact, the foundation of machine learning can be attributed to physical concepts.
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This book serves as an introduction to the growing field of quantum many-body transport in interacting nanojunctions.
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Among resummation techniques for perturbative QCD in the context of collider and flavor physics, soft-collinear effective theory (SCET) has emerged as... Læs mere
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Based on the workshop of the same name, this proceedings volume presents selected research investigating the mathematics of collective phenomena emerging from quantum theory at observable scales.
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This text presents a collection of mathematical exercises with the aim of guiding readers to study topics in statistical physics, equilibrium thermodynamics, information theory, and their various connections.
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This book delves into the foundational principles governing the treatment of molecular networks and "chemical space"—the comprehensive domain encompassing all physically achievable molecules—from the perspectives of vector space, graph theory, and data science.
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This book explores Lieb's Simplified approach to the ground state of systems of interacting bosons.
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This monograph aims to offer a concise introduction to optimal transport, quickly transitioning to its applications in statistics and machine learning. As such, this monograph is suitable for a graduate course on the topic of statistical optimal transport.
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The measurement is performed in an invariant mass region of 116 GeV to 1500 GeV as a function of invariant mass and absolute rapidity of the l^+l^-- pair, and as a function of invariant mass and pseudorapidity separation of the l^+l^-- pair.
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Carroll "The Multiversal book series is equally unique, providing book-length extensions of the... Læs mere
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This book addresses research challenges in the rapidly developing area of nonequilibrium thermodynamics and fluctuation kinetics.