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  • Reduction, Approximation, Machine Learning, Surrogates, Emulators and Simulators

    RAMSES

    Collections series Mathematics and Statistics (R0)
    This volume is focused on the review of recent algorithmic and mathematical advances and the development of new research directions for Mathematical Model Approximations via RAMSES (Reduced order models, Approximation theory, Machine learning, Surrogates, Emulators, Simulators) in the setting of parametrized partial differential equations also with sparse and noisy data in high-dimensional ... En savoir plus

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  • Quantification of Uncertainty: Improving Efficiency and Technology

    QUIET selected contributions

    Collections series Mathematics and Statistics (R0)
    This book explores four guiding themes – reduced order modelling, high dimensional problems, efficient algorithms, and applications – by reviewing recent algorithmic and mathematical advances and the development of new research directions for uncertainty quantification in the context of partial differential equations with random inputs. Highlighting the most promising approaches for (near-) future ... En savoir plus

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    A core principle of physics is knowledge gained from data. Thus, deep learning has instantly entered physics and may become a new paradigm in basic and applied research.This textbook addresses physics students and physicists who want to understand what deep learning actually means, and what is the potential for their own scientific projects. Being familiar with linear algebra and parameter ... En savoir plus

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  • Signal Processing for Neuroscientists, A Companion Volume

    Advanced Topics, Nonlinear Techniques and Multi-Channel Analysis

    The popularity of signal processing in neuroscience is increasing, and with the current availability and development of computer hardware and software, it is anticipated that the current growth will continue. Because electrode fabrication has improved and measurement equipment is getting less expensive, electrophysiological measurements with large numbers of channels are now very common. In ... En savoir plus

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  • Mathematics Of Autonomy: Mathematical Methods For Cyber-physical-cognitive Systems

    Mathematics of Autonomy provides solid mathematical foundations for building useful Autonomous Systems. It clarifies what makes a system autonomous rather than simply automated, and reveals the inherent limitations of systems currently incorrectly labeled as autonomous in reference to the specific and strong uncertainty that characterizes the environments they operate in. Such complex real-world ... En savoir plus

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  • Process Modelling and Model Analysis

    Collections Livre 4 - Process Systems Engineering
    Process Modelling and Model Analysis describes the use of models in process engineering. Process engineering is all about manufacturing--of just about anything! To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. For example, process engineers would apply models ... En savoir plus

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  • Artificial Intelligence for Scientific Discoveries

    Extracting Physical Concepts from Experimental Data Using Deep Learning

    par Raban Iten ...
    Collections series Physics and Astronomy (R0)
    Will research soon be done by artificial intelligence, thereby making human researchers superfluous? This book explains modern approaches to discovering physical concepts with machine learning and elucidates their strengths and limitations. The automation of the creation of experimental setups and physical models, as well as model testing are discussed. The focus of the book is the automation of ... En savoir plus

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  • Science: Image In Action - Proceedings Of The 7th International Workshop On Data Analysis In Astronomy "Livio Scarsi And Vito Digesu"

    Collections series The Science And Culture Series - Astrophysics
    The book gathers articles that were exposed during the seventh edition of the Workshop “Data Analysis in Astronomy”. It illustrates a current trend to search for common expressions or models transcending usual disciplines, possibly associated with some lack in the Mathematics required to model complex systems. In that, data analysis would be at the epicentre and a key facilitator of some current ... En savoir plus

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  • Manifold Learning

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    Collections series Computer Science (R0)
    This Open Access book reviews recent theoretical and numerical developments in nonlinear model order reduction in continuum mechanics, being addressed to Master and PhD students, as well as to researchers, lecturers and instructors. The aim of the authors is to provide tools for a better understanding and implement reduced order models by using: physics-based models, synthetic data forecast by ... En savoir plus

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  • Statistical Methods for Materials Science

    The Data Science of Microstructure Characterization

    Data analytics has become an integral part of materials science. This book provides the practical tools and fundamentals needed for researchers in materials science to understand how to analyze large datasets using statistical methods, especially inverse methods applied to microstructure characterization. It contains valuable guidance on essential topics such as denoising and data modeling. ... En savoir plus

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  • Image Fusion

    Algorithms and Applications

    par Tania Stathaki ...
    The growth in the use of sensor technology has led to the demand for image fusion: signal processing techniques that can combine information received from different sensors into a single composite image in an efficient and reliable manner. This book brings together classical and modern algorithms and design architectures, demonstrating through applications how these can be implemented. Image ... En savoir plus

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  • System Identification

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    Collections series Engineering (R0)
    System Identification shows the student reader how to approach the system identification problem in a systematic fashion. The process is divided into three basic steps: experimental design and data collection; model structure selection and parameter estimation; and model validation, each of which is the subject of one or more parts of the text.Following an introduction on system theory, ... En savoir plus

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