Case Studies in Neural Data Analysis

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Author :
Publisher : MIT Press
ISBN 13 : 0262529378
Total Pages : 385 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Case Studies in Neural Data Analysis by : Mark A. Kramer

Download or read book Case Studies in Neural Data Analysis written by Mark A. Kramer and published by MIT Press. This book was released on 2016-11-04 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data. As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis. The book begins with an introduction to MATLAB, the most common programming platform in neuroscience, which is used in the book. (Readers familiar with MATLAB can skip this chapter and might decide to focus on data type or method type.) The book goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each chapter offers a stand-alone case study that can be used separately as part of a targeted investigation. The book includes some mathematical discussion but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying MATLAB code are freely available on the authors' website. The book can be used for upper-level undergraduate or graduate courses or as a professional reference. A version of this textbook with all of the examples in Python is available on the MIT Press website.

Unifying Causality and Psychology

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Publisher : Springer
ISBN 13 : 3319240943
Total Pages : 962 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Unifying Causality and Psychology by : Gerald Young

Download or read book Unifying Causality and Psychology written by Gerald Young and published by Springer. This book was released on 2016-05-17 with total page 962 pages. Available in PDF, EPUB and Kindle. Book excerpt: This magistral treatise approaches the integration of psychology through the study of the multiple causes of normal and dysfunctional behavior. Causality is the focal point reviewed across disciplines. Using diverse models, the book approaches unifying psychology as an ongoing project that integrates genetics, experience, evolution, brain, development, change mechanisms, and so on. The book includes in its integration free will, epitomized as freedom in being. It pinpoints the role of the self in causality and the freedom we have in determining our own behavior. The book deals with disturbed behavior, as well, and tackles the DSM-5 approach to mental disorder and the etiology of psychopathology. Young examines all these topics with a critical eye, and gives many innovative ideas and models that will stimulate thinking on the topic of psychology and causality for decades to come. It is truly integrative and original. Among the topics covered: Models and systems of causality of behavior. Nature and nurture: evolution and complexities. Early adversity, fetal programming, and getting under the skin. Free will in psychotherapy: helping people believe. Causality in psychological injury and law: basics and critics. A Neo-Piagetian/Neo-Eriksonian 25-step (sub)stage model. Unifying Causality and Psychology appeals to the disciplines of psychology, psychiatry, epidemiology, philosophy, neuroscience, genetics, law, the social sciences and humanistic fields, in general, and other mental health fields. Its level of writing makes it appropriate for graduate courses, as well as researchers and practitioners.

Graph Embedding Methods for Multiple-Omics Data Analysis

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2889716007
Total Pages : 220 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Graph Embedding Methods for Multiple-Omics Data Analysis by : Chen Qingfeng

Download or read book Graph Embedding Methods for Multiple-Omics Data Analysis written by Chen Qingfeng and published by Frontiers Media SA. This book was released on 2021-11-08 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Independent Component Analysis

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Publisher : John Wiley & Sons
ISBN 13 : 0471464198
Total Pages : 505 pages
Book Rating : 4.4/5 (714 download)

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Book Synopsis Independent Component Analysis by : Aapo Hyvärinen

Download or read book Independent Component Analysis written by Aapo Hyvärinen and published by John Wiley & Sons. This book was released on 2004-04-05 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive introduction to ICA for students and practitioners Independent Component Analysis (ICA) is one of the most exciting new topics in fields such as neural networks, advanced statistics, and signal processing. This is the first book to provide a comprehensive introduction to this new technique complete with the fundamental mathematical background needed to understand and utilize it. It offers a general overview of the basics of ICA, important solutions and algorithms, and in-depth coverage of new applications in image processing, telecommunications, audio signal processing, and more. Independent Component Analysis is divided into four sections that cover: * General mathematical concepts utilized in the book * The basic ICA model and its solution * Various extensions of the basic ICA model * Real-world applications for ICA models Authors Hyvarinen, Karhunen, and Oja are well known for their contributions to the development of ICA and here cover all the relevant theory, new algorithms, and applications in various fields. Researchers, students, and practitioners from a variety of disciplines will find this accessible volume both helpful and informative.

Philosophical Transactions

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Publisher :
ISBN 13 :
Total Pages : 812 pages
Book Rating : 4.E/5 ( download)

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Book Synopsis Philosophical Transactions by :

Download or read book Philosophical Transactions written by and published by . This book was released on 2005 with total page 812 pages. Available in PDF, EPUB and Kindle. Book excerpt: Each issue of Transactions B is devoted to a specific area of the biological sciences, including clinical science. All papers are peer reviewed and edited to the highest standards. Published on the 29th of each month, Transactions B is essential reading for all biologists.

ECAI 2023

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Publisher : IOS Press
ISBN 13 : 164368437X
Total Pages : 3328 pages
Book Rating : 4.6/5 (436 download)

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Book Synopsis ECAI 2023 by : K. Gal

Download or read book ECAI 2023 written by K. Gal and published by IOS Press. This book was released on 2023-10-18 with total page 3328 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrate innovative applications and uses of advanced AI technology. ECAI 2023 received 1896 submissions – a record number – of which 1691 were retained for review, ultimately resulting in an acceptance rate of 23%. The 390 papers included here, cover topics including machine learning, natural language processing, multi agent systems, and vision and knowledge representation and reasoning. PAIS 2023 received 17 submissions, of which 10 were accepted after a rigorous review process. Those 10 papers cover topics ranging from fostering better working environments, behavior modeling and citizen science to large language models and neuro-symbolic applications, and are also included here. Presenting a comprehensive overview of current research and developments in AI, the book will be of interest to all those working in the field.

De novo Molecular Design

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Publisher : John Wiley & Sons
ISBN 13 : 3527677038
Total Pages : 540 pages
Book Rating : 4.5/5 (276 download)

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Book Synopsis De novo Molecular Design by : Gisbert Schneider

Download or read book De novo Molecular Design written by Gisbert Schneider and published by John Wiley & Sons. This book was released on 2013-10-10 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Systematically examining current methods and strategies, this ready reference covers a wide range of molecular structures, from organic-chemical drugs to peptides, Proteins and nucleic acids, in line with emerging new drug classes derived from biomacromolecules. A leader in the field and one of the pioneers of this young discipline has assembled here the most prominent experts from across the world to provide first-hand knowledge. While most of their methods and examples come from the area of pharmaceutical discovery and development, the approaches are equally applicable for chemical probes and diagnostics, pesticides, and any other molecule designed to interact with a biological system. Numerous images and screenshots illustrate the many examples and method descriptions. With its broad and balanced coverage, this will be the firststop resource not only for medicinal chemists, biochemists and biotechnologists, but equally for bioinformaticians and molecular designers for many years to come. From the content: * Reaction-driven de novo design * Adaptive methods in molecular design * Design of ligands against multitarget profiles * Free energy methods in ligand design * Fragment-based de novo design * Automated design of focused and target family-oriented compound libraries * Molecular de novo design by nature-inspired computing * 3D QSAR approaches to de novo drug design * Bioisosteres in de novo design * De novo design of peptides, proteins and nucleic acid structures, including RNA aptamers and many more.

Population Genetics, Quantitative Genetics and Animal Improvement

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Publisher :
ISBN 13 :
Total Pages : 804 pages
Book Rating : 4.:/5 (89 download)

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Book Synopsis Population Genetics, Quantitative Genetics and Animal Improvement by : Michael P. H. Stumpf

Download or read book Population Genetics, Quantitative Genetics and Animal Improvement written by Michael P. H. Stumpf and published by . This book was released on 2005 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Geometry of Deep Learning

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Author :
Publisher : Springer Nature
ISBN 13 : 9811660468
Total Pages : 338 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Geometry of Deep Learning by : Jong Chul Ye

Download or read book Geometry of Deep Learning written by Jong Chul Ye and published by Springer Nature. This book was released on 2022-01-05 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The focus of this book is on providing students with insights into geometry that can help them understand deep learning from a unified perspective. Rather than describing deep learning as an implementation technique, as is usually the case in many existing deep learning books, here, deep learning is explained as an ultimate form of signal processing techniques that can be imagined. To support this claim, an overview of classical kernel machine learning approaches is presented, and their advantages and limitations are explained. Following a detailed explanation of the basic building blocks of deep neural networks from a biological and algorithmic point of view, the latest tools such as attention, normalization, Transformer, BERT, GPT-3, and others are described. Here, too, the focus is on the fact that in these heuristic approaches, there is an important, beautiful geometric structure behind the intuition that enables a systematic understanding. A unified geometric analysis to understand the working mechanism of deep learning from high-dimensional geometry is offered. Then, different forms of generative models like GAN, VAE, normalizing flows, optimal transport, and so on are described from a unified geometric perspective, showing that they actually come from statistical distance-minimization problems. Because this book contains up-to-date information from both a practical and theoretical point of view, it can be used as an advanced deep learning textbook in universities or as a reference source for researchers interested in acquiring the latest deep learning algorithms and their underlying principles. In addition, the book has been prepared for a codeshare course for both engineering and mathematics students, thus much of the content is interdisciplinary and will appeal to students from both disciplines.

HCI International 2023 – Late Breaking Papers

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Publisher : Springer Nature
ISBN 13 : 3031480384
Total Pages : 698 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis HCI International 2023 – Late Breaking Papers by : Masaaki Kurosu

Download or read book HCI International 2023 – Late Breaking Papers written by Masaaki Kurosu and published by Springer Nature. This book was released on 2023-11-24 with total page 698 pages. Available in PDF, EPUB and Kindle. Book excerpt: This seven-volume set LNCS 14054-14060 constitutes the proceedings of the 25th International Conference, HCI International 2023, in Copenhagen, Denmark, in July 2023. For the HCCII 2023 proceedings, a total of 1578 papers and 396 posters was carefully reviewed and selected from 7472 submissions. Additionally, 267 papers and 133 posters are included in the volumes of the proceedings published after the conference, as “Late Breaking Work”. These papers were organized in the following topical sections: HCI Design and User Experience; Cognitive Engineering and Augmented Cognition; Cultural Issues in Design; Technologies for the Aging Population; Accessibility and Design for All; Designing for Health and Wellbeing; Information Design, Visualization, Decision-making and Collaboration; Social Media, Creative Industries and Cultural Digital Experiences; Digital Human Modeling, Ergonomics and Safety; HCI in Automated Vehicles and Intelligent Transportation; Sustainable Green Smart Cities and Smart Industry; eXtended Reality Interactions; Gaming and Gamification Experiences; Interacting with Artificial Intelligence; Security, Privacy, Trust and Ethics; Learning Technologies and Learning Experiences; eCommerce, Digital Marketing and eFinance.

Artificial Intelligence in Bioinformatics and Drug Repurposing: Methods and Applications

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Author :
Publisher : Frontiers Media SA
ISBN 13 : 2889748812
Total Pages : 167 pages
Book Rating : 4.8/5 (897 download)

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Book Synopsis Artificial Intelligence in Bioinformatics and Drug Repurposing: Methods and Applications by : Pan Zheng

Download or read book Artificial Intelligence in Bioinformatics and Drug Repurposing: Methods and Applications written by Pan Zheng and published by Frontiers Media SA. This book was released on 2022-04-08 with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Graph Representation Learning

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Publisher : Springer Nature
ISBN 13 : 3031015886
Total Pages : 141 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Graph Representation Learning by : William L. William L. Hamilton

Download or read book Graph Representation Learning written by William L. William L. Hamilton and published by Springer Nature. This book was released on 2022-06-01 with total page 141 pages. Available in PDF, EPUB and Kindle. Book excerpt: Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Graphical Models, Exponential Families, and Variational Inference

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Publisher : Now Publishers Inc
ISBN 13 : 1601981848
Total Pages : 324 pages
Book Rating : 4.6/5 (19 download)

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Book Synopsis Graphical Models, Exponential Families, and Variational Inference by : Martin J. Wainwright

Download or read book Graphical Models, Exponential Families, and Variational Inference written by Martin J. Wainwright and published by Now Publishers Inc. This book was released on 2008 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: The core of this paper is a general set of variational principles for the problems of computing marginal probabilities and modes, applicable to multivariate statistical models in the exponential family.

Active Inference

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Publisher : MIT Press
ISBN 13 : 0262362287
Total Pages : 313 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Active Inference by : Thomas Parr

Download or read book Active Inference written by Thomas Parr and published by MIT Press. This book was released on 2022-03-29 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first comprehensive treatment of active inference, an integrative perspective on brain, cognition, and behavior used across multiple disciplines. Active inference is a way of understanding sentient behavior—a theory that characterizes perception, planning, and action in terms of probabilistic inference. Developed by theoretical neuroscientist Karl Friston over years of groundbreaking research, active inference provides an integrated perspective on brain, cognition, and behavior that is increasingly used across multiple disciplines including neuroscience, psychology, and philosophy. Active inference puts the action into perception. This book offers the first comprehensive treatment of active inference, covering theory, applications, and cognitive domains. Active inference is a “first principles” approach to understanding behavior and the brain, framed in terms of a single imperative to minimize free energy. The book emphasizes the implications of the free energy principle for understanding how the brain works. It first introduces active inference both conceptually and formally, contextualizing it within current theories of cognition. It then provides specific examples of computational models that use active inference to explain such cognitive phenomena as perception, attention, memory, and planning.

Proceedings of the 1993 Connectionist Models Summer School

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Publisher : Psychology Press
ISBN 13 : 1317780531
Total Pages : 424 pages
Book Rating : 4.3/5 (177 download)

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Book Synopsis Proceedings of the 1993 Connectionist Models Summer School by : Michael C. Mozer

Download or read book Proceedings of the 1993 Connectionist Models Summer School written by Michael C. Mozer and published by Psychology Press. This book was released on 2014-03-05 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: The result of the 1993 Connectionist Models Summer School, the papers in this volume exemplify the tremendous breadth and depth of research underway in the field of neural networks. Although the slant of the summer school has always leaned toward cognitive science and artificial intelligence, the diverse scientific backgrounds and research interests of accepted students and invited faculty reflect the broad spectrum of areas contributing to neural networks, including artificial intelligence, cognitive science, computer science, engineering, mathematics, neuroscience, and physics. Providing an accurate picture of the state of the art in this fast-moving field, the proceedings of this intense two-week program of lectures, workshops, and informal discussions contains timely and high-quality work by the best and the brightest in the neural networks field.

An Introduction to Variational Autoencoders

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Publisher :
ISBN 13 : 9781680836226
Total Pages : 102 pages
Book Rating : 4.8/5 (362 download)

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Book Synopsis An Introduction to Variational Autoencoders by : Diederik P. Kingma

Download or read book An Introduction to Variational Autoencoders written by Diederik P. Kingma and published by . This book was released on 2019-11-12 with total page 102 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Introduction to Variational Autoencoders provides a quick summary for the of a topic that has become an important tool in modern-day deep learning techniques.

Statistical Parametric Mapping: The Analysis of Functional Brain Images

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Publisher : Elsevier
ISBN 13 : 0080466508
Total Pages : 689 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis Statistical Parametric Mapping: The Analysis of Functional Brain Images by : William D. Penny

Download or read book Statistical Parametric Mapping: The Analysis of Functional Brain Images written by William D. Penny and published by Elsevier. This book was released on 2011-04-28 with total page 689 pages. Available in PDF, EPUB and Kindle. Book excerpt: In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. - An essential reference and companion for users of the SPM software - Provides a complete description of the concepts and procedures entailed by the analysis of brain images - Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data - Stands as a compendium of all the advances in neuroimaging data analysis over the past decade - Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes - Structured treatment of data analysis issues that links different modalities and models - Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible