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.

Causal Inference

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Publisher : CRC Press
ISBN 13 : 9781420076165
Total Pages : 352 pages
Book Rating : 4.0/5 (761 download)

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Book Synopsis Causal Inference by : Miquel A. Hernan

Download or read book Causal Inference written by Miquel A. Hernan and published by CRC Press. This book was released on 2019-07-07 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: The application of causal inference methods is growing exponentially in fields that deal with observational data. Written by pioneers in the field, this practical book presents an authoritative yet accessible overview of the methods and applications of causal inference. With a wide range of detailed, worked examples using real epidemiologic data as well as software for replicating the analyses, the text provides a thorough introduction to the basics of the theory for non-time-varying treatments and the generalization to complex longitudinal data.

Information Theory, Inference and Learning Algorithms

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Publisher : Cambridge University Press
ISBN 13 : 9780521642989
Total Pages : 694 pages
Book Rating : 4.6/5 (429 download)

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Book Synopsis Information Theory, Inference and Learning Algorithms by : David J. C. MacKay

Download or read book Information Theory, Inference and Learning Algorithms written by David J. C. MacKay and published by Cambridge University Press. This book was released on 2003-09-25 with total page 694 pages. Available in PDF, EPUB and Kindle. Book excerpt: Information theory and inference, taught together in this exciting textbook, lie at the heart of many important areas of modern technology - communication, signal processing, data mining, machine learning, pattern recognition, computational neuroscience, bioinformatics and cryptography. The book introduces theory in tandem with applications. Information theory is taught alongside practical communication systems such as arithmetic coding for data compression and sparse-graph codes for error-correction. Inference techniques, including message-passing algorithms, Monte Carlo methods and variational approximations, are developed alongside applications to clustering, convolutional codes, independent component analysis, and neural networks. Uniquely, the book covers state-of-the-art error-correcting codes, including low-density-parity-check codes, turbo codes, and digital fountain codes - the twenty-first-century standards for satellite communications, disk drives, and data broadcast. Richly illustrated, filled with worked examples and over 400 exercises, some with detailed solutions, the book is ideal for self-learning, and for undergraduate or graduate courses. It also provides an unparalleled entry point for professionals in areas as diverse as computational biology, financial engineering and machine learning.

Statistical Inference

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Publisher : CRC Press
ISBN 13 : 1040024025
Total Pages : 1746 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Statistical Inference by : George Casella

Download or read book Statistical Inference written by George Casella and published by CRC Press. This book was released on 2024-05-23 with total page 1746 pages. Available in PDF, EPUB and Kindle. Book excerpt: This classic textbook builds theoretical statistics from the first principles of probability theory. Starting from the basics of probability, the authors develop the theory of statistical inference using techniques, definitions, and concepts that are statistical and natural extensions, and consequences, of previous concepts. It covers all topics from a standard inference course including: distributions, random variables, data reduction, point estimation, hypothesis testing, and interval estimation. Features The classic graduate-level textbook on statistical inference Develops elements of statistical theory from first principles of probability Written in a lucid style accessible to anyone with some background in calculus Covers all key topics of a standard course in inference Hundreds of examples throughout to aid understanding Each chapter includes an extensive set of graduated exercises Statistical Inference, Second Edition is primarily aimed at graduate students of statistics, but can be used by advanced undergraduate students majoring in statistics who have a solid mathematics background. It also stresses the more practical uses of statistical theory, being more concerned with understanding basic statistical concepts and deriving reasonable statistical procedures, while less focused on formal optimality considerations. This is a reprint of the second edition originally published by Cengage Learning, Inc. in 2001.

Human Inference

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Publisher : Prentice Hall
ISBN 13 :
Total Pages : 362 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis Human Inference by : Richard E. Nisbett

Download or read book Human Inference written by Richard E. Nisbett and published by Prentice Hall. This book was released on 1980 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Elements of Causal Inference

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Publisher : MIT Press
ISBN 13 : 0262037319
Total Pages : 289 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis Elements of Causal Inference by : Jonas Peters

Download or read book Elements of Causal Inference written by Jonas Peters and published by MIT Press. This book was released on 2017-11-29 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning. The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data. After explaining the need for causal models and discussing some of the principles underlying causal inference, the book teaches readers how to use causal models: how to compute intervention distributions, how to infer causal models from observational and interventional data, and how causal ideas could be exploited for classical machine learning problems. All of these topics are discussed first in terms of two variables and then in the more general multivariate case. The bivariate case turns out to be a particularly hard problem for causal learning because there are no conditional independences as used by classical methods for solving multivariate cases. The authors consider analyzing statistical asymmetries between cause and effect to be highly instructive, and they report on their decade of intensive research into this problem. The book is accessible to readers with a background in machine learning or statistics, and can be used in graduate courses or as a reference for researchers. The text includes code snippets that can be copied and pasted, exercises, and an appendix with a summary of the most important technical concepts.

Inference to the Best Explanation

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Publisher : Taylor & Francis
ISBN 13 : 9780415242035
Total Pages : 236 pages
Book Rating : 4.2/5 (42 download)

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Book Synopsis Inference to the Best Explanation by : Peter Lipton

Download or read book Inference to the Best Explanation written by Peter Lipton and published by Taylor & Francis. This book was released on 2004 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inference to the Best Explanation is an unrivalled exposition of a theory of particular interest to students both of epistemology and the philosophy of science.

Reading Between the Lines

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Publisher : Routledge
ISBN 13 : 1351705903
Total Pages : 186 pages
Book Rating : 4.3/5 (517 download)

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Book Synopsis Reading Between the Lines by : Catherine Delamain

Download or read book Reading Between the Lines written by Catherine Delamain and published by Routledge. This book was released on 2017-07-05 with total page 186 pages. Available in PDF, EPUB and Kindle. Book excerpt: Suitable for teachers and speech and language therapists working in the fields of language and literacy, and concerned with developing inferencing skills in their students, this book contains a collection of 300 texts which are graded, and lead the student gradually from simple tasks.

Causal Inference in Statistics, Social, and Biomedical Sciences

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Publisher : Cambridge University Press
ISBN 13 : 0521885884
Total Pages : 647 pages
Book Rating : 4.5/5 (218 download)

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Book Synopsis Causal Inference in Statistics, Social, and Biomedical Sciences by : Guido W. Imbens

Download or read book Causal Inference in Statistics, Social, and Biomedical Sciences written by Guido W. Imbens and published by Cambridge University Press. This book was released on 2015-04-06 with total page 647 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Model Selection and Multimodel Inference

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Publisher : Springer Science & Business Media
ISBN 13 : 0387224564
Total Pages : 512 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis Model Selection and Multimodel Inference by : Kenneth P. Burnham

Download or read book Model Selection and Multimodel Inference written by Kenneth P. Burnham and published by Springer Science & Business Media. This book was released on 2007-05-28 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.

Causal Inference

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Publisher : Yale University Press
ISBN 13 : 0300255888
Total Pages : 585 pages
Book Rating : 4.3/5 (2 download)

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Book Synopsis Causal Inference by : Scott Cunningham

Download or read book Causal Inference written by Scott Cunningham and published by Yale University Press. This book was released on 2021-01-26 with total page 585 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible, contemporary introduction to the methods for determining cause and effect in the Social Sciences “Causation versus correlation has been the basis of arguments—economic and otherwise—since the beginning of time. Causal Inference: The Mixtape uses legit real-world examples that I found genuinely thought-provoking. It’s rare that a book prompts readers to expand their outlook; this one did for me.”—Marvin Young (Young MC) Causal inference encompasses the tools that allow social scientists to determine what causes what. In a messy world, causal inference is what helps establish the causes and effects of the actions being studied—for example, the impact (or lack thereof) of increases in the minimum wage on employment, the effects of early childhood education on incarceration later in life, or the influence on economic growth of introducing malaria nets in developing regions. Scott Cunningham introduces students and practitioners to the methods necessary to arrive at meaningful answers to the questions of causation, using a range of modeling techniques and coding instructions for both the R and the Stata programming languages.

Argument and Inference

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Publisher : MIT Press
ISBN 13 : 0262337770
Total Pages : 283 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Argument and Inference by : Gregory Johnson

Download or read book Argument and Inference written by Gregory Johnson and published by MIT Press. This book was released on 2017-01-06 with total page 283 pages. Available in PDF, EPUB and Kindle. Book excerpt: A thorough and practical introduction to inductive logic with a focus on arguments and the rules used for making inductive inferences. This textbook offers a thorough and practical introduction to inductive logic. The book covers a range of different types of inferences with an emphasis throughout on representing them as arguments. This allows the reader to see that, although the rules and guidelines for making each type of inference differ, the purpose is always to generate a probable conclusion. After explaining the basic features of an argument and the different standards for evaluating arguments, the book covers inferences that do not require precise probabilities or the probability calculus: the induction by confirmation, inference to the best explanation, and Mill's methods. The second half of the book presents arguments that do require the probability calculus, first explaining the rules of probability, and then the proportional syllogism, inductive generalization, and Bayes' rule. Each chapter ends with practice problems and their solutions. Appendixes offer additional material on deductive logic, odds, expected value, and (very briefly) the foundations of probability. Argument and Inference can be used in critical thinking courses. It provides these courses with a coherent theme while covering the type of reasoning that is most often used in day-to-day life and in the natural, social, and medical sciences. Argument and Inference is also suitable for inductive logic and informal logic courses, as well as philosophy of sciences courses that need an introductory text on scientific and inductive methods.

Causation, Evidence, and Inference

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Publisher : Routledge
ISBN 13 : 1317675886
Total Pages : 285 pages
Book Rating : 4.3/5 (176 download)

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Book Synopsis Causation, Evidence, and Inference by : Julian Reiss

Download or read book Causation, Evidence, and Inference written by Julian Reiss and published by Routledge. This book was released on 2015-05-22 with total page 285 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, Reiss argues in favor of a tight fit between evidence, concept and purpose in our causal investigations in the sciences. There is no doubt that the sciences employ a vast array of techniques to address causal questions such as controlled experiments, randomized trials, statistical and econometric tools, causal modeling and thought experiments. But how do these different methods relate to each other and to the causal inquiry at hand? Reiss argues that there is no "gold standard" in settling causal issues against which other methods can be measured. Rather, the various methods of inference tend to be good only relative to certain interpretations of the word "cause", and each interpretation, in turn, helps to address some salient purpose (prediction, explanation or policy analysis) but not others. The main objective of this book is to explore the metaphysical and methodological consequences of this view in the context of numerous cases studies from the natural and social sciences.

Explanation in Causal Inference

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Publisher : Oxford University Press, USA
ISBN 13 : 0199325871
Total Pages : 729 pages
Book Rating : 4.1/5 (993 download)

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Book Synopsis Explanation in Causal Inference by : Tyler J. VanderWeele

Download or read book Explanation in Causal Inference written by Tyler J. VanderWeele and published by Oxford University Press, USA. This book was released on 2015 with total page 729 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive examination of methods for mediation and interaction, VanderWeele's book is the first to approach this topic from the perspective of causal inference. Numerous software tools are provided, and the text is both accessible and easy to read, with examples drawn from diverse fields. The result is an essential reference for anyone conducting empirical research in the biomedical or social sciences.

Inferences during Reading

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Publisher : Cambridge University Press
ISBN 13 : 131629904X
Total Pages : 439 pages
Book Rating : 4.3/5 (162 download)

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Book Synopsis Inferences during Reading by : Edward J. O'Brien

Download or read book Inferences during Reading written by Edward J. O'Brien and published by Cambridge University Press. This book was released on 2015-04-16 with total page 439 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inferencing is defined as 'the act of deriving logical conclusions from premises known or assumed to be true', and it is one of the most important processes necessary for successful comprehension during reading. This volume features contributions by distinguished researchers in cognitive psychology, educational psychology, and neuroscience on topics central to our understanding of the inferential process during reading. The chapters cover aspects of inferencing that range from the fundamental bottom-up processes that form the basis for an inference to occur, to the more strategic processes that transpire when a reader is engaged in literary understanding of a text. Basic activation mechanisms, word-level inferencing, methodological considerations, inference validation, causal inferencing, emotion, development of inferences processes as a skill, embodiment, contributions from neuroscience, and applications to naturalistic text are all covered as well as expository text, online learning materials, and literary immersion.

Introducing Inference

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Publisher :
ISBN 13 : 9780923573386
Total Pages : 113 pages
Book Rating : 4.5/5 (733 download)

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Book Synopsis Introducing Inference by : Marilyn M. Toomey

Download or read book Introducing Inference written by Marilyn M. Toomey and published by . This book was released on 2000 with total page 113 pages. Available in PDF, EPUB and Kindle. Book excerpt:

The Foundations of Scientific Inference

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Publisher : University of Pittsburgh Pre
ISBN 13 : 0822971259
Total Pages : 170 pages
Book Rating : 4.8/5 (229 download)

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Book Synopsis The Foundations of Scientific Inference by : Wesley Salmon

Download or read book The Foundations of Scientific Inference written by Wesley Salmon and published by University of Pittsburgh Pre. This book was released on 1967-09 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: Not since Ernest Nagel’s 1939 monograph on the theory of probability has there been a comprehensive elementary survey of the philosophical problems of probablity and induction. This is an authoritative and up-to-date treatment of the subject, and yet it is relatively brief and nontechnical. Hume’s skeptical arguments regarding the justification of induction are taken as a point of departure, and a variety of traditional and contemporary ways of dealing with this problem are considered. The author then sets forth his own criteria of adequacy for interpretations of probability. Utilizing these criteria he analyzes contemporary theories of probability, as well as the older classical and subjective interpretations.