Neural Foundations

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Unsupervised Learning

Author : Geoffrey Hinton
Publisher : MIT Press
ISBN 13 : 9780262581684
Total Pages : 420 pages
Book Rating : 4.5/5 (816 download)

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Book Synopsis Unsupervised Learning by : Geoffrey Hinton

Download or read book Unsupervised Learning written by Geoffrey Hinton and published by MIT Press. This book was released on 1999-05-24 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. This volume of Foundations of Neural Computation, on unsupervised learning algorithms, focuses on neural network learning algorithms that do not require an explicit teacher. The goal of unsupervised learning is to extract an efficient internal representation of the statistical structure implicit in the inputs. These algorithms provide insights into the development of the cerebral cortex and implicit learning in humans. They are also of interest to engineers working in areas such as computer vision and speech recognition who seek efficient representations of raw input data.

Neural Network Learning

Author : Martin Anthony
Publisher : Cambridge University Press
ISBN 13 : 052157353X
Total Pages : 405 pages
Book Rating : 4.5/5 (215 download)

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Book Synopsis Neural Network Learning by : Martin Anthony

Download or read book Neural Network Learning written by Martin Anthony and published by Cambridge University Press. This book was released on 1999-11-04 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work explores probabilistic models of supervised learning problems and addresses the key statistical and computational questions. Chapters survey research on pattern classification with binary-output networks, including a discussion of the relevance of the Vapnik Chervonenkis dimension, and of estimates of the dimension for several neural network models. In addition, the authors develop a model of classification by real-output networks, and demonstrate the usefulness of classification...

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Author : Nikola K. Kasabov
Publisher : Marcel Alencar
ISBN 13 : 0262112124
Total Pages : 581 pages
Book Rating : 4.2/5 (621 download)

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Book Synopsis Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering by : Nikola K. Kasabov

Download or read book Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering written by Nikola K. Kasabov and published by Marcel Alencar. This book was released on 1996 with total page 581 pages. Available in PDF, EPUB and Kindle. Book excerpt: Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.

Foundations of Neural Development

Author : S Marc Breedlove
Publisher : Sinauer
ISBN 13 : 9781605355795
Total Pages : 380 pages
Book Rating : 4.3/5 (557 download)

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Book Synopsis Foundations of Neural Development by : S Marc Breedlove

Download or read book Foundations of Neural Development written by S Marc Breedlove and published by Sinauer. This book was released on 2017-03-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foundations of Neural Development is an accessible textbook, written with a conversational style and topics appropriate for an undergraduate audience. Each chapter begins with a thought-provoking vignette, or a real-life story, that the subsequent material illuminates. The “Researchers at Work” feature, available in every chapter, describes a classic study in detail, taking the reader through the hypothesis, test, result, and conclusion of an experiment. Other features include a marginal glossary, review questions, and bulleted summary in each chapter. Chapters 1–7 unfold in the order of ontogeny, covering induction, the establishment of a body plan, neural migration, differentiation, axonal pathfinding, synapse formation, and apoptosis. Chapters 8–10 address activity-guided, experience-guided, and socially guided neural development—mechanisms that were crucial for the evolution of the human brain. Lively and engaging, with the finest illustrations, this is the perfect book to help any undergraduate student understand how a single microscopic cell, a human zygote, can develop into the most complex machine on earth, the brain./div

Single Neuron Computation

Author : Thomas M. McKenna
Publisher : Academic Press
ISBN 13 : 1483296067
Total Pages : 663 pages
Book Rating : 4.4/5 (832 download)

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Book Synopsis Single Neuron Computation by : Thomas M. McKenna

Download or read book Single Neuron Computation written by Thomas M. McKenna and published by Academic Press. This book was released on 2014-05-19 with total page 663 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains twenty-two original contributions that provide a comprehensive overview of computational approaches to understanding a single neuron structure. The focus on cellular-level processes is twofold. From a computational neuroscience perspective, a thorough understanding of the information processing performed by single neurons leads to an understanding of circuit- and systems-level activity. From the standpoint of artificial neural networks (ANNs), a single real neuron is as complex an operational unit as an entire ANN, and formalizing the complex computations performed by real neurons is essential to the design of enhanced processor elements for use in the next generation of ANNs.The book covers computation in dendrites and spines, computational aspects of ion channels, synapses, patterned discharge and multistate neurons, and stochastic models of neuron dynamics. It is the most up-to-date presentation of biophysical and computational methods.

Graphical Models

Author : Michael Irwin Jordan
Publisher : MIT Press
ISBN 13 : 9780262600422
Total Pages : 450 pages
Book Rating : 4.6/5 (4 download)

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Book Synopsis Graphical Models by : Michael Irwin Jordan

Download or read book Graphical Models written by Michael Irwin Jordan and published by MIT Press. This book was released on 2001 with total page 450 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithm and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Graphical models use graphs to represent and manipulate joint probability distributions. They have their roots in artificial intelligence, statistics, and neural networks. The clean mathematical formalism of the graphical models framework makes it possible to understand a wide variety of network-based approaches to computation, and in particular to understand many neural network algorithms and architectures as instances of a broader probabilistic methodology. It also makes it possible to identify novel features of neural network algorithms and architectures and to extend them to more general graphical models.This book exemplifies the interplay between the general formal framework of graphical models and the exploration of new algorithms and architectures. The selections range from foundational papers of historical importance to results at the cutting edge of research. Contributors H. Attias, C. M. Bishop, B. J. Frey, Z. Ghahramani, D. Heckerman, G. E. Hinton, R. Hofmann, R. A. Jacobs, Michael I. Jordan, H. J. Kappen, A. Krogh, R. Neal, S. K. Riis, F. B. Rodríguez, L. K. Saul, Terrence J. Sejnowski, P. Smyth, M. E. Tipping, V. Tresp, Y. Weiss

Graph Neural Networks: Foundations, Frontiers, and Applications

Author : Lingfei Wu
Publisher : Springer Nature
ISBN 13 : 9811660549
Total Pages : 701 pages
Book Rating : 4.8/5 (116 download)

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Book Synopsis Graph Neural Networks: Foundations, Frontiers, and Applications by : Lingfei Wu

Download or read book Graph Neural Networks: Foundations, Frontiers, and Applications written by Lingfei Wu and published by Springer Nature. This book was released on 2022-01-03 with total page 701 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning. This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.

Neuronal Dynamics

Author : Wulfram Gerstner
Publisher : Cambridge University Press
ISBN 13 : 1107060834
Total Pages : 591 pages
Book Rating : 4.1/5 (7 download)

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Book Synopsis Neuronal Dynamics by : Wulfram Gerstner

Download or read book Neuronal Dynamics written by Wulfram Gerstner and published by Cambridge University Press. This book was released on 2014-07-24 with total page 591 pages. Available in PDF, EPUB and Kindle. Book excerpt: This solid introduction uses the principles of physics and the tools of mathematics to approach fundamental questions of neuroscience.

Neural-Symbolic Learning Systems

Author : Artur S. d'Avila Garcez
Publisher : Springer Science & Business Media
ISBN 13 : 1447102118
Total Pages : 276 pages
Book Rating : 4.4/5 (471 download)

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Book Synopsis Neural-Symbolic Learning Systems by : Artur S. d'Avila Garcez

Download or read book Neural-Symbolic Learning Systems written by Artur S. d'Avila Garcez and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence is concerned with producing devices that help or replace human beings in their daily activities. Neural-symbolic learning systems play a central role in this task by combining, and trying to benefit from, the advantages of both the neural and symbolic paradigms of artificial intelligence. This book provides a comprehensive introduction to the field of neural-symbolic learning systems, and an invaluable overview of the latest research issues in this area. It is divided into three sections, covering the main topics of neural-symbolic integration - theoretical advances in knowledge representation and learning, knowledge extraction from trained neural networks, and inconsistency handling in neural-symbolic systems. Each section provides a balance of theory and practice, giving the results of applications using real-world problems in areas such as DNA sequence analysis, power systems fault diagnosis, and software requirements specifications. Neural-Symbolic Learning Systems will be invaluable reading for researchers and graduate students in Engineering, Computing Science, Artificial Intelligence, Machine Learning and Neurocomputing. It will also be of interest to Intelligent Systems practitioners and anyone interested in applications of hybrid artificial intelligence systems.

An Introduction to Neural Information Retrieval

Author : Bhaskar Mitra
Publisher : Foundations and Trends (R) in Information Retrieval
ISBN 13 : 9781680835328
Total Pages : 142 pages
Book Rating : 4.8/5 (353 download)

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Book Synopsis An Introduction to Neural Information Retrieval by : Bhaskar Mitra

Download or read book An Introduction to Neural Information Retrieval written by Bhaskar Mitra and published by Foundations and Trends (R) in Information Retrieval. This book was released on 2018-12-23 with total page 142 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficient Query Processing for Scalable Web Search will be a valuable reference for researchers and developers working on This tutorial provides an accessible, yet comprehensive, overview of the state-of-the-art of Neural Information Retrieval.

Biophysical Neural Networks

Author : Roman R. Poznanski
Publisher :
ISBN 13 :
Total Pages : 522 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Biophysical Neural Networks by : Roman R. Poznanski

Download or read book Biophysical Neural Networks written by Roman R. Poznanski and published by . This book was released on 2001 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Neural Basis of Free Will

Author : Peter Tse
Publisher : MIT Press
ISBN 13 : 0262019108
Total Pages : 473 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis The Neural Basis of Free Will by : Peter Tse

Download or read book The Neural Basis of Free Will written by Peter Tse and published by MIT Press. This book was released on 2013 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: The issues of mental causation, consciousness, and free will have vexed philosophers since Plato. This book examines these unresolved issues from a neuroscientific perspective. In contrast with philosophers who use logic rather than data to argue whether mental causation or consciousness can exist given unproven first assumptions, Tse proposes that we instead listen to what neurons have to say. Because the brain must already embody a solution to the mind--body problem, why not focus on how the brain actually realizes mental causation? Tse draws on exciting recent neuroscientific data concerning how informational causation is realized in physical causation at the level of NMDA receptors, synapses, dendrites, neurons, and neuronal circuits. He argues that a particular kind of strong free will and downward mental causation are realized in rapid synaptic plasticity. Recent neurophysiological breakthroughs reveal that neurons function as criterial assessors of their inputs, which then change the criteria that will make other neurons fire in the future. Such informational causation cannot change the physical basis of information realized in the present, but it can change the physical basis of information that may be realized in the immediate future. This gets around the standard argument against free will centered on the impossibility of self-causation. Tse explores the ways that mental causation and qualia might be realized in this kind of neuronal and associated information-processing architecture, and considers the psychological and philosophical implications of having such an architecture realized in our brains.

Foundations of Neuroscience

Author : Casey Henley
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (125 download)

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Book Synopsis Foundations of Neuroscience by : Casey Henley

Download or read book Foundations of Neuroscience written by Casey Henley and published by . This book was released on 2021 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Neurobiology of Brain and Behavioral Development

Author : Robbin Gibb
Publisher : Academic Press
ISBN 13 : 012804084X
Total Pages : 497 pages
Book Rating : 4.1/5 (28 download)

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Book Synopsis The Neurobiology of Brain and Behavioral Development by : Robbin Gibb

Download or read book The Neurobiology of Brain and Behavioral Development written by Robbin Gibb and published by Academic Press. This book was released on 2017-10-23 with total page 497 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Neurobiology of Brain and Behavioral Development provides an overview of the process of brain development, including recent discoveries on how the brain develops. This book collates and integrates these findings, weaving the latest information with core information on the neurobiology of brain development. It focuses on cortical development, but also features discussions on how the other parts of the brain wire into the developing cerebral cortex. A systems approach is used to describe the anatomical underpinnings of behavioral development, connecting anatomical and molecular features of brain development with behavioral development.The disruptors of typical brain development are discussed in appropriate sections, as is the science of epigenetics that presents a novel and instructive approach on how experiences, both individual and intergenerational, can alter features of brain development. What distinguishes this book from others in the field is its focus on both molecular mechanisms and behavioral outcomes. This body of knowledge contributes to our understanding of the fundamentals of brain plasticity and metaplasticity, both of which are also showcased in this book. - Provides an up-to-date overview of the process of brain development that is suitable for use as a university textbook at an early graduate or senior undergraduate level - Breadth from molecular level (Chapters 5-7) to the behavioral/cognitive level (Chapters 8-12), beginning with Chapters 1-4 providing a historical context of the ideas - Integrates the neurobiology of brain development and behavior, promoting the idea that animal models inform human development - Presents an emphasis on the role of epigenetics and brain plasticity in brain development and behavior

Neural Codes and Distributed Representations

Author : L. F. Abbott
Publisher : MIT Press
ISBN 13 : 9780262511001
Total Pages : 378 pages
Book Rating : 4.5/5 (11 download)

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Book Synopsis Neural Codes and Distributed Representations by : L. F. Abbott

Download or read book Neural Codes and Distributed Representations written by L. F. Abbott and published by MIT Press. This book was released on 1999 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since its founding in 1989 by Terrence Sejnowski, Neural Computation has become the leading journal in the field. Foundations of Neural Computation collects, by topic, the most significant papers that have appeared in the journal over the past nine years. The present volume focuses on neural codes and representations, topics of broad interest to neuroscientists and modelers. The topics addressed are: how neurons encode information through action potential firing patterns, how populations of neurons represent information, and how individual neurons use dendritic processing and biophysical properties of synapses to decode spike trains. The papers encompass a wide range of levels of investigation, from dendrites and neurons to networks and systems.

Deep Learning

Author : Josh Patterson
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491914211
Total Pages : 550 pages
Book Rating : 4.4/5 (919 download)

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Book Synopsis Deep Learning by : Josh Patterson

Download or read book Deep Learning written by Josh Patterson and published by "O'Reilly Media, Inc.". This book was released on 2017-07-28 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool Learn how to use DL4J natively on Spark and Hadoop

Where Mathematics Come From How The Embodied Mind Brings Mathematics Into Being

Author : George Lakoff
Publisher :
ISBN 13 :
Total Pages : 520 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Where Mathematics Come From How The Embodied Mind Brings Mathematics Into Being by : George Lakoff

Download or read book Where Mathematics Come From How The Embodied Mind Brings Mathematics Into Being written by George Lakoff and published by . This book was released on 2000-11-02 with total page 520 pages. Available in PDF, EPUB and Kindle. Book excerpt: A study of the cognitive science of mathematical ideas.