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Geometric Structures Of Information
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Book Synopsis Geometric Structures of Information by : Frank Nielsen
Download or read book Geometric Structures of Information written by Frank Nielsen and published by Springer. This book was released on 2018-11-19 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on information geometry manifolds of structured data/information and their advanced applications featuring new and fruitful interactions between several branches of science: information science, mathematics and physics. It addresses interrelations between different mathematical domains like shape spaces, probability/optimization & algorithms on manifolds, relational and discrete metric spaces, computational and Hessian information geometry, algebraic/infinite dimensional/Banach information manifolds, divergence geometry, tensor-valued morphology, optimal transport theory, manifold & topology learning, and applications like geometries of audio-processing, inverse problems and signal processing. The book collects the most important contributions to the conference GSI’2017 – Geometric Science of Information.
Book Synopsis Geometric Structures of Statistical Physics, Information Geometry, and Learning by : Frédéric Barbaresco
Download or read book Geometric Structures of Statistical Physics, Information Geometry, and Learning written by Frédéric Barbaresco and published by Springer Nature. This book was released on 2021-06-27 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning and artificial intelligence increasingly use methodological tools rooted in statistical physics. Conversely, limitations and pitfalls encountered in AI question the very foundations of statistical physics. This interplay between AI and statistical physics has been attested since the birth of AI, and principles underpinning statistical physics can shed new light on the conceptual basis of AI. During the last fifty years, statistical physics has been investigated through new geometric structures allowing covariant formalization of the thermodynamics. Inference methods in machine learning have begun to adapt these new geometric structures to process data in more abstract representation spaces. This volume collects selected contributions on the interplay of statistical physics and artificial intelligence. The aim is to provide a constructive dialogue around a common foundation to allow the establishment of new principles and laws governing these two disciplines in a unified manner. The contributions were presented at the workshop on the Joint Structures and Common Foundation of Statistical Physics, Information Geometry and Inference for Learning which was held in Les Houches in July 2020. The various theoretical approaches are discussed in the context of potential applications in cognitive systems, machine learning, signal processing.
Book Synopsis Geometric Structure of High-Dimensional Data and Dimensionality Reduction by : Jianzhong Wang
Download or read book Geometric Structure of High-Dimensional Data and Dimensionality Reduction written by Jianzhong Wang and published by Springer Science & Business Media. This book was released on 2012-04-28 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Geometric Structure of High-Dimensional Data and Dimensionality Reduction" adopts data geometry as a framework to address various methods of dimensionality reduction. In addition to the introduction to well-known linear methods, the book moreover stresses the recently developed nonlinear methods and introduces the applications of dimensionality reduction in many areas, such as face recognition, image segmentation, data classification, data visualization, and hyperspectral imagery data analysis. Numerous tables and graphs are included to illustrate the ideas, effects, and shortcomings of the methods. MATLAB code of all dimensionality reduction algorithms is provided to aid the readers with the implementations on computers. The book will be useful for mathematicians, statisticians, computer scientists, and data analysts. It is also a valuable handbook for other practitioners who have a basic background in mathematics, statistics and/or computer algorithms, like internet search engine designers, physicists, geologists, electronic engineers, and economists. Jianzhong Wang is a Professor of Mathematics at Sam Houston State University, U.S.A.
Book Synopsis Differential Geometric Structures by : Walter A. Poor
Download or read book Differential Geometric Structures written by Walter A. Poor and published by Courier Corporation. This book was released on 2015-04-27 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: This introductory text defines geometric structure by specifying parallel transport in an appropriate fiber bundle and focusing on simplest cases of linear parallel transport in a vector bundle. 1981 edition.
Book Synopsis Geometric Data Structures for Computer Graphics by : Elmar Langetepe
Download or read book Geometric Data Structures for Computer Graphics written by Elmar Langetepe and published by A K Peters/CRC Press. This book was released on 2006 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on algorithms and geometric data structures that have proven to be versatile, efficient and fundamental. It endows practitioners in the computer graphics field with a working knowledge of a wide range of geometric data structures from computational geometry.
Book Synopsis Geometric Science of Information by : Frank Nielsen
Download or read book Geometric Science of Information written by Frank Nielsen and published by Springer Nature. This book was released on 2021-07-14 with total page 929 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 5th International Conference on Geometric Science of Information, GSI 2021, held in Paris, France, in July 2021. The 98 papers presented in this volume were carefully reviewed and selected from 125 submissions. They cover all the main topics and highlights in the domain of geometric science of information, including information geometry manifolds of structured data/information and their advanced applications. The papers are organized in the following topics: Probability and statistics on Riemannian Manifolds; sub-Riemannian geometry and neuromathematics; shapes spaces; geometry of quantum states; geometric and structure preserving discretizations; information geometry in physics; Lie group machine learning; geometric and symplectic methods for hydrodynamical models; harmonic analysis on Lie groups; statistical manifold and Hessian information geometry; geometric mechanics; deformed entropy, cross-entropy, and relative entropy; transformation information geometry; statistics, information and topology; geometric deep learning; topological and geometrical structures in neurosciences; computational information geometry; manifold and optimization; divergence statistics; optimal transport and learning; and geometric structures in thermodynamics and statistical physics.
Book Synopsis Modern Geometric Structures and Fields by : Сергей Петрович Новиков
Download or read book Modern Geometric Structures and Fields written by Сергей Петрович Новиков and published by American Mathematical Soc.. This book was released on 2006 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents the basics of Riemannian geometry in its modern form as geometry of differentiable manifolds and the important structures on them. This book shows that Riemannian geometry has a great influence to several fundamental areas of modern mathematics and its applications.
Book Synopsis Geometric Theory of Information by : Frank Nielsen
Download or read book Geometric Theory of Information written by Frank Nielsen and published by Springer Science & Business Media. This book was released on 2014-05-08 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together geometric tools and their applications for Information analysis. It collects current and many uses of in the interdisciplinary fields of Information Geometry Manifolds in Advanced Signal, Image & Video Processing, Complex Data Modeling and Analysis, Information Ranking and Retrieval, Coding, Cognitive Systems, Optimal Control, Statistics on Manifolds, Machine Learning, Speech/sound recognition and natural language treatment which are also substantially relevant for the industry.
Book Synopsis Foliations and Geometric Structures by : Aurel Bejancu
Download or read book Foliations and Geometric Structures written by Aurel Bejancu and published by Springer Science & Business Media. This book was released on 2006-01-17 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Offers basic material on distributions and foliations. This book introduces and builds the tools needed for studying the geometry of foliated manifolds. Its main theme is to investigate the interrelations between foliations of a manifold on the one hand, and the many geometric structures that the manifold may admit on the other hand.
Book Synopsis Information Geometry and Its Applications by : Shun-ichi Amari
Download or read book Information Geometry and Its Applications written by Shun-ichi Amari and published by Springer. This book was released on 2016-02-02 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first comprehensive book on information geometry, written by the founder of the field. It begins with an elementary introduction to dualistic geometry and proceeds to a wide range of applications, covering information science, engineering, and neuroscience. It consists of four parts, which on the whole can be read independently. A manifold with a divergence function is first introduced, leading directly to dualistic structure, the heart of information geometry. This part (Part I) can be apprehended without any knowledge of differential geometry. An intuitive explanation of modern differential geometry then follows in Part II, although the book is for the most part understandable without modern differential geometry. Information geometry of statistical inference, including time series analysis and semiparametric estimation (the Neyman–Scott problem), is demonstrated concisely in Part III. Applications addressed in Part IV include hot current topics in machine learning, signal processing, optimization, and neural networks. The book is interdisciplinary, connecting mathematics, information sciences, physics, and neurosciences, inviting readers to a new world of information and geometry. This book is highly recommended to graduate students and researchers who seek new mathematical methods and tools useful in their own fields.
Book Synopsis A Geometric Approach to the Unification of Symbolic Structures and Neural Networks by : Tiansi Dong
Download or read book A Geometric Approach to the Unification of Symbolic Structures and Neural Networks written by Tiansi Dong and published by Springer Nature. This book was released on 2020-08-24 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: The unification of symbolist and connectionist models is a major trend in AI. The key is to keep the symbolic semantics unchanged. Unfortunately, present embedding approaches cannot. The approach in this book makes the unification possible. It is indeed a new and promising approach in AI. -Bo Zhang, Director of AI Institute, Tsinghua It is indeed wonderful to see the reviving of the important theme Nural Symbolic Model. Given the popularity and prevalence of deep learning, symbolic processing is often neglected or downplayed. This book confronts this old issue head on, with a historical look, incorporating recent advances and new perspectives, thus leading to promising new methods and approaches. -Ron Sun (RPI), on Governing Board of Cognitive Science Society Both for language and humor, approaches like those described in this book are the way to snickerdoodle wombats. -Christian F. Hempelmann (Texas A&M-Commerce) on Executive Board of International Society for Humor Studies
Download or read book Information Geometry written by Nihat Ay and published by Springer. This book was released on 2017-08-25 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides a comprehensive introduction and a novel mathematical foundation of the field of information geometry with complete proofs and detailed background material on measure theory, Riemannian geometry and Banach space theory. Parametrised measure models are defined as fundamental geometric objects, which can be both finite or infinite dimensional. Based on these models, canonical tensor fields are introduced and further studied, including the Fisher metric and the Amari-Chentsov tensor, and embeddings of statistical manifolds are investigated. This novel foundation then leads to application highlights, such as generalizations and extensions of the classical uniqueness result of Chentsov or the Cramér-Rao inequality. Additionally, several new application fields of information geometry are highlighted, for instance hierarchical and graphical models, complexity theory, population genetics, or Markov Chain Monte Carlo. The book will be of interest to mathematicians who are interested in geometry, information theory, or the foundations of statistics, to statisticians as well as to scientists interested in the mathematical foundations of complex systems.
Book Synopsis Structures: A Geometric Approach by : Edmond Saliklis
Download or read book Structures: A Geometric Approach written by Edmond Saliklis and published by Springer. This book was released on 2018-11-07 with total page 332 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graphic methods for structural design essentially translate problems of algebra into geometric representations, allowing solutions to be reached using geometric construction (ie: drawing pictures) instead of tedious and error-prone arithmetic. This was the common method before the invention of calculators and computers, but had been largely abandoned in the last half century in favor of numerical techniques. However, in recent years the convenience and ease of graphic statics has made a comeback in architecture and engineering. Several professors have begun using graphic statics in the classroom.and.studio environment. But until now, there had been no guidebook that rapidly brings students up to speed on the fundamentals of how to create graphical solutions to statics problems.Graphic Statics introduces all of the traditional graphic statics techniques in a parametric drawing format, using the free program GeoGebra. Then, advanced topics such as indeterminate beams and three dimensional curved surfaces are be covered. Along the way, links to wider design ideas are introduced in a succinct summary of the steps needed to create elegant solutions to many staticequilibrium problems.Meant for students in civil and architectural engineering, architecture,and construction, this practical introduction will also be useful to professionals looking to add the power of graphic statics to their work.
Book Synopsis Geometric Structures by : Douglas B. Aichele
Download or read book Geometric Structures written by Douglas B. Aichele and published by Prentice Hall. This book was released on 2007-04 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: For prospective elementary and middle school teachers. This text provides a creative, inquiry-based experience with geometry that is appropriate for prospective elementary and middle school teachers. The coherent series of text activities supports each student's growth toward being a confident, independent learner empowered with the help of peers to make sense of the geometric world. This curriculum is explicitly developed to provide future elementary and middle school teachers with experience recalling and appropriately using standard geometry ideas, experience learning and making sense of new geometry, experience discussing geometry with peers, experience asking questions about geometry, experience listening and understanding as others talk about geometry, experience gaining meaning from reading geometry, experience expressing geometry ideas through writing, experience thinking about geometry, and experience doing geometry. These activities constitute an "inquiry based" curriculum. In this style of learning and teaching, whole class discussions and group work replace listening to lectures as the dominant class activity.
Book Synopsis Handbook of Geometric Topology by : R.B. Sher
Download or read book Handbook of Geometric Topology written by R.B. Sher and published by Elsevier. This book was released on 2001-12-20 with total page 1145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geometric Topology is a foundational component of modern mathematics, involving the study of spacial properties and invariants of familiar objects such as manifolds and complexes. This volume, which is intended both as an introduction to the subject and as a wide ranging resouce for those already grounded in it, consists of 21 expository surveys written by leading experts and covering active areas of current research. They provide the reader with an up-to-date overview of this flourishing branch of mathematics.
Book Synopsis Information, Entropy and Their Geometric Structures by : Frédéric Barbaresco
Download or read book Information, Entropy and Their Geometric Structures written by Frédéric Barbaresco and published by MDPI. This book was released on 2018-10-04 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a printed edition of the Special Issue "Information, Entropy and Their Geometric Structures" that was published in Entropy
Book Synopsis New Geometric Data Structures for Collision Detection and Haptics by : René Weller
Download or read book New Geometric Data Structures for Collision Detection and Haptics written by René Weller and published by Springer Science & Business Media. This book was released on 2013-07-12 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Starting with novel algorithms for optimally updating bounding volume hierarchies of objects undergoing arbitrary deformations, the author presents a new data structure that allows, for the first time, the computation of the penetration volume. The penetration volume is related to the water displacement of the overlapping region, and thus corresponds to a physically motivated and continuous force. The practicability of the approaches used is shown by realizing new applications in the field of robotics and haptics, including a user study that evaluates the influence of the degrees of freedom in complex haptic interactions. New Geometric Data Structures for Collision Detection and Haptics closes by proposing an open source benchmarking suite that evaluates both the performance and the quality of the collision response in order to guarantee a fair comparison of different collision detection algorithms. Required in the fields of computer graphics, physically-based simulations, computer animations, robotics and haptics, collision detection is a fundamental problem that arises every time we interact with virtual objects. Some of the open challenges associated with collision detection include the handling of deformable objects, the stable computation of physically-plausible contact information, and the extremely high frequencies that are required for haptic rendering. New Geometric Data Structures for Collision Detection and Haptics presents new solutions to all of these challenges, and will prove to be a valuable resource for researchers and practitioners of collision detection in the haptics, robotics and computer graphics and animation domains.
