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Data-Driven Computational Neuroscience: Machine Learning and Statistical Models, Concha Bielza, Pedro Larranaga


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Автор: Concha Bielza, Pedro Larranaga
Название:  Data-Driven Computational Neuroscience: Machine Learning and Statistical Models
ISBN: 9781108493703
Издательство: Cambridge Academ
Классификация:






ISBN-10: 110849370X
Обложка/Формат: Hardcover
Страницы: 700
Вес: 1.58 кг.
Дата издания: 31.08.2020
Серия: Psychology
Язык: English
Иллюстрации: Worked examples or exercises; 40 line drawings, color; 210 line drawings, black and white
Размер: 185 x 259 x 45
Читательская аудитория: Professional and scholarly
Ключевые слова: Cognition & cognitive psychology,Signal processing,Machine learning,Neural networks & fuzzy systems,Neurosciences, COMPUTERS / Computer Vision & Pattern Recognition
Подзаголовок: Machine learning and statistical models
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: Data-driven computational neuroscience facilitates the transformation of data into insights into the structure and functions of the brain. This modern treatment of real world cases offers neuroscience researchers and graduate students a comprehensive, in-depth guide to statistical and machine learning methods.


Computational Models for Neuroscience

Автор: Robert Hecht-Nielsen; Thomas McKenna
Название: Computational Models for Neuroscience
ISBN: 1447111117 ISBN-13(EAN): 9781447111115
Издательство: Springer
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Цена: 18284.00 р.
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Описание: At this epoch, neuroscience is like a huge collection of small, jagged, jigsaw puz- zle pieces piled in a mound in a large warehouse (with neuroscientists going in and tossing more pieces onto the mound every month).

Theoretical And Computational Models Of Word Learning

Автор: Gogate & Hollich
Название: Theoretical And Computational Models Of Word Learning
ISBN: 1466629738 ISBN-13(EAN): 9781466629738
Издательство: Mare Nostrum (Eurospan)
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Цена: 25502.00 р.
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Описание: The process of learning words and languages may seem like an instinctual trait, inherent to nearly all humans from a young age. However, a vast range of complex research and information exists in detailing the complexities of the process of word learning. <br><br><em>Theoretical and Computational Models of Word Learning: Trends in Psychology and Artificial Intelligence</em> strives to combine cross-disciplinary research into one comprehensive volume to help readers gain a fuller understanding of the developmental processes and influences that makeup the progression of word learning. Blending together developmental psychology and artificial intelligence, this publication is intended for researchers, practitioners, and educators who are interested in language learning and its development as well as computational models formed from these specific areas of research.

Computational Neuroscience Models of the Basal Ganglia

Автор: Chakravarthy
Название: Computational Neuroscience Models of the Basal Ganglia
ISBN: 9811084939 ISBN-13(EAN): 9789811084935
Издательство: Springer
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Цена: 20962.00 р.
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Описание: The book is a compendium of the aforementioned subclass of models of Basal Ganglia, which presents some the key existent theories of Basal Ganglia function. The book presents computational models of basal ganglia-related disorders, including Parkinson’s disease, schizophrenia, and addiction. Importantly, it highlights the applications of understanding the role of the basal ganglia to treat neurological and psychiatric disorders. The purpose of the present book is to amend and expand on James Houk’s book (MIT press; ASIN: B010BF4U9K) by providing a comprehensive overview on computational models of the basal ganglia. This book caters to researchers and academics from the area of computational cognitive neuroscience.

A Computational Approach to Statistical Learning

Автор: Arnold
Название: A Computational Approach to Statistical Learning
ISBN: 113804637X ISBN-13(EAN): 9781138046375
Издательство: Taylor&Francis
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Цена: 12554.00 р.
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Описание: A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods. The text contains annotated code to over 80 original reference functions. These functions provide minimal working implementations of common statistical learning algorithms. Every chapter concludes with a fully worked out application that illustrates predictive modeling tasks using a real-world dataset. The text begins with a detailed analysis of linear models and ordinary least squares. Subsequent chapters explore extensions such as ridge regression, generalized linear models, and additive models. The second half focuses on the use of general-purpose algorithms for convex optimization and their application to tasks in statistical learning. Models covered include the elastic net, dense neural networks, convolutional neural networks (CNNs), and spectral clustering. A unifying theme throughout the text is the use of optimization theory in the description of predictive models, with a particular focus on the singular value decomposition (SVD). Through this theme, the computational approach motivates and clarifies the relationships between various predictive models. Taylor Arnold is an assistant professor of statistics at the University of Richmond. His work at the intersection of computer vision, natural language processing, and digital humanities has been supported by multiple grants from the National Endowment for the Humanities (NEH) and the American Council of Learned Societies (ACLS). His first book, Humanities Data in R, was published in 2015. Michael Kane is an assistant professor of biostatistics at Yale University. He is the recipient of grants from the National Institutes of Health (NIH), DARPA, and the Bill and Melinda Gates Foundation. His R package bigmemory won the Chamber's prize for statistical software in 2010. Bryan Lewis is an applied mathematician and author of many popular R packages, including irlba, doRedis, and threejs.

Computational Neuroscience Models of the Basal Ganglia

Автор: V. Srinivasa Chakravarthy; Ahmed A. Moustafa
Название: Computational Neuroscience Models of the Basal Ganglia
ISBN: 9811341680 ISBN-13(EAN): 9789811341687
Издательство: Springer
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Цена: 22359.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: The book is a compendium of the aforementioned subclass of models of Basal Ganglia, which presents some the key existent theories of Basal Ganglia function. The book presents computational models of basal ganglia-related disorders, including Parkinson’s disease, schizophrenia, and addiction. Importantly, it highlights the applications of understanding the role of the basal ganglia to treat neurological and psychiatric disorders. The purpose of the present book is to amend and expand on James Houk’s book (MIT press; ASIN: B010BF4U9K) by providing a comprehensive overview on computational models of the basal ganglia. This book caters to researchers and academics from the area of computational cognitive neuroscience.

Computational Neuroscience

Автор: Wanpracha Chaovalitwongse; Panos Pardalos; Petros
Название: Computational Neuroscience
ISBN: 1461425999 ISBN-13(EAN): 9781461425991
Издательство: Springer
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Цена: 27951.00 р.
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Описание: This volume includes contributions from numerous disciplines, bridging a vital gap between the mathematical sciences and neuroscience research. This book demonstrates how methods from data mining, signal processing, optimization and cutting-edge medical techniques can be used to tackle the most challenging modern neuroscience problems.

Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges

Автор: Oscar Camara; Tommaso Mansi; Mihaela Pop; Kawal Rh
Название: Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges
ISBN: 3642542670 ISBN-13(EAN): 9783642542671
Издательство: Springer
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Цена: 6429.00 р.
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the 4th International Workshop on Statistical Atlases and Computational Models of the Heart: Imaging and Modelling Challenges, STACOM 2013, held in conjunction with MICCAI 2013, in Nagoya, Japan, in September 2013.

Computational Neuroscience of Drug Addiction

Автор: Boris Gutkin; Serge H. Ahmed
Название: Computational Neuroscience of Drug Addiction
ISBN: 1461429404 ISBN-13(EAN): 9781461429401
Издательство: Springer
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Цена: 28732.00 р.
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Описание: This book describes the torrent of data generated through research on the neurobiology and psychology of drug addiction, and discusses the role of mathematical and computational modeling in the development of more testable and rigorous models of addiction.

Computational Neuroscience and Cognitive Modelling

Автор: Anderson Britt
Название: Computational Neuroscience and Cognitive Modelling
ISBN: 1446249301 ISBN-13(EAN): 9781446249307
Издательство: Sage Publications
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Цена: 9504.00 р.
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Описание: This unique, self-contained and accessible textbook provides an introduction to computational modelling in psychology and neuroscience accessible to students with little or no background in computing or mathematics.


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