Thomas Trappenberg's Books

Fundamentals of Machine Learning

By: Thomas P. Trappenberg,Thomas Trappenberg

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Fundamentals of Machine Learning

By: Thomas P. Trappenberg,Thomas Trappenberg

Interest in machine learning is exploding across the world, both in research and for industrial applications. Fundamentals of Machine Learning provides a brief and accessible introduction to this rapidly growing field, one that will appeal to both students and researchers.

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260

Published Date

ISBN 10

0198828047

ISBN 13

9780198828044

Fundamentals of Computational Neuroscience

By: Thomas Trappenberg

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Fundamentals of Computational Neuroscience

By: Thomas Trappenberg

The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the first edition. Completely redesigned and revised, it introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain.

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Page Count

417

Publisher

Oxford University Press

Published Date

ISBN 10

0199568413

ISBN 13

9780199568413

Fundamentals of Machine Learning

By: Thomas P. Trappenberg,Thomas Trappenberg

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Fundamentals of Machine Learning

By: Thomas P. Trappenberg,Thomas Trappenberg

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260

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ISBN 10

0198828047

ISBN 13

9780198828044

Fundamentals of Computational Neuroscience

By: Thomas Trappenberg

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Fundamentals of Computational Neuroscience

By: Thomas Trappenberg

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417

Publisher

Oxford University Press

Published Date

ISBN 10

0199568413

ISBN 13

9780199568413

Principles Of Phase Structures In Particle Physics

By: Hildegard Meyer-ortmanns,Thomas Reisz

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Principles Of Phase Structures In Particle Physics

By: Hildegard Meyer-ortmanns,Thomas Reisz

The phase structure of particle physics shows up in matter at extremely high densities and/or temperatures as they were reached in the early universe, shortly after the big bang, or in heavy-ion collisions, as they are performed nowadays in laboratory experiments. In contrast to phase transitions of condensed matter physics, the underlying fundamental theories are better known than their macroscopic manifestations in phase transitions. These theories are quantum chromodynamics for the strong interaction part and the electroweak part of the Standard Model for the electroweak interaction. It is their non-Abelian gauge structure that makes it a big challenge to predict the type of phase conversion between phases of different symmetries and different particle contents. The book is about a variety of analytical and numerical tools that are needed to study the phase structure of particle physics. To these belong convergent and asymptotic expansions in strong and weak couplings, dimensional reduction, renormalization group studies, gap equations, Monte Carlo simulations with and without fermions, finite-size and finite-mass scaling analyses, and the approach of effective actions as supplement to first-principle calculations.

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Page Count

702

Publisher

World Scientific

Published Date

ISBN 10

9814496278

ISBN 13

9789814496278

Fundamentals of Computational Neuroscience

Third Edition

By: Thomas P. Trappenberg

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Fundamentals of Computational Neuroscience

Third Edition

By: Thomas P. Trappenberg

Computational neuroscience is the theoretical study of the brain to uncover the principles and mechanisms that guide the development, organization, information processing, and mental functions of the nervous system. Although not a new area, it is only recently that enough knowledge has been gathered to establish computational neuroscience as a scientific discipline in its own right. Given the complexity of the field, and its increasing importance in progressing our understanding of how the brain works, there has long been a need for an introductory text on what is often assumed to be an impenetrable topic. The new edition of Fundamentals of Computational Neuroscience build on the success and strengths of the previous editions. It introduces the theoretical foundations of neuroscience with a focus on the nature of information processing in the brain. The book covers the introduction and motivation of simplified models of neurons that are suitable for exploring information processing in large brain-like networks. Additionally, it introduces several fundamental network architectures and discusses their relevance for information processing in the brain, giving some examples of models of higher-order cognitive functions to demonstrate the advanced insight that can be gained with such studies. Each chapter starts by introducing its topic with experimental facts and conceptual questions related to the study of brain function. An additional feature is the inclusion of simple Matlab programs that can be used to explore many of the mechanisms explained in the book. An accompanying webpage includes programs for download. The book will be the essential text for anyone in the brain sciences who wants to get to grips with this topic.

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Page Count

411

Publisher

Oxford University Press

Published Date

ISBN 10

0192696130

ISBN 13

9780192696137

On Copula Density Estimation and Measures of Multivariate Association

By: Thomas Blumentritt

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On Copula Density Estimation and Measures of Multivariate Association

By: Thomas Blumentritt

Measuring the degree of association between random variables is a task inherent in many practical applications such as risk management and financial modeling. Well-known measures like Spearman's rho and Kendall's tau can be expressed in terms of the underlying copula only, hence, being independent of the underlying univariate marginal distributions. Opposed to these classical measures of association, mutual information, which is derived from information theory, constitutes a fundamentally different approach of measuring association. Although this measure is likewise independent of the univariate margins, it is not a functional of the copula but of the corresponding copula density. Besides the theoretical properties of mutual information as a measure of multivariate association, possibilities to estimate the copula density based on observations of continuous distributions are investigated. To cope with the effect of boundary bias, new estimators are introduced and existing functionals are generalized to the multivariate case. The performance of these estimators is evaluated in comparison to common kernel density estimation schemes. To facilitate variance estimation by means of resampling methods like bootstrapping, an algorithm is introduced, which significantly reduces computation time in comparison with pre-implemented algorithms. In practical applications, complete continuous data is oftentimes not available to the analyst. Instead, categorial data derived from the underlying continuous distribution may be given. Hence, estimation of the copula and its density based on contingency tables is investigated. The newly developed estimators are employed to derive estimates of Spearman's rho and Kendall's tau and their performance is compared.

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Page Count

202

Publisher

BoD – Books on Demand

Published Date

ISBN 10

3844101217

ISBN 13

9783844101218

Principles of Neural Science, Fifth Edition

By: Eric R. Kandel,James H. Schwartz,Thomas M. Jessell,Steven A. Siegelbaum,A. J. Hudspeth

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Principles of Neural Science, Fifth Edition

By: Eric R. Kandel,James H. Schwartz,Thomas M. Jessell,Steven A. Siegelbaum,A. J. Hudspeth

The field's definitive work from a Nobel Prize-winning author 900 full-color illustrations Principles of Neural Science, 5e describes our current understanding of how the nerves, brain, and mind function. From molecules to anatomic structures and systems to cognitive function, this comprehensive reference covers all aspects of neuroscience. Widely regarded as the field’s cornerstone reference, the fifth edition is highlighted by more than 900 full-color illustrations. The fifth edition has been completely updated to reflect the tremendous amount of new research and development in neuroscience in the last decade. Lead author Eric Kandel was awarded the Nobel Prize in Physiology or Medicine in 2000.

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Page Count

1760

Publisher

McGraw Hill Professional

Published Date

ISBN 10

0071810013

ISBN 13

9780071810012

Fundamentals of Computational Neuroscience

Third Edition

By: Thomas Trappenberg

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Fundamentals of Computational Neuroscience

Third Edition

By: Thomas Trappenberg

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Page Count

411

Publisher

Oxford University Press

Published Date

ISBN 10

0192696122

ISBN 13

9780192696120

Fundamentals of Computational Neuroscience

By: Thomas P. Trappenberg

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Fundamentals of Computational Neuroscience

By: Thomas P. Trappenberg

This title includes the following features: An accessible introduction to the field of computational neuroscience; Aimed at graduate/postgraduates upwards in the cognitive and brain sciences; Accompanying webpage with MATLAB programmes to download; Affordable

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Page Count

338

Publisher

Oxford : Oxford University Press

Published Date

ISBN 10

0198515820

ISBN 13

9780198515821

Book's by Thomas Trappenberg

Fundamentals of Machine Learning

Fundamentals of Machine Learning

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience

Fundamentals of Machine Learning

Fundamentals of Machine Learning

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience

Principles Of Phase Structures In Particle Physics

Principles Of Phase Structures In Particle Physics

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience

On Copula Density Estimation and Measures of Multivariate Association

On Copula Density Estimation and Measures of Multivariate Association

Principles of Neural Science, Fifth Edition

Principles of Neural Science, Fifth Edition

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience

Fundamentals of Computational Neuroscience

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