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Information Theory, Inference and Learning Algorithms
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, independ...
Active Inference
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 a...
Inference to the Best Explanation
How do we go about weighing evidence, testing hypotheses, and making inferences? According to the model of Inference to the Best Explanation, we work out what to infer from the evidence by thinking about what would actually explain that evidence, and we take the ability of a hypothesis to explain the evidence as a sign that the hypothesis is correct. In Inference to the Best Explanation, Peter Lipton gives this important and influential idea the development and assessment it deserves. The second edition has been substantially enlarged and reworked, with a new chapter on the relationship between explanation and Bayesianism, and an extension and defence of the account of contrastive explanation. It also includes an expanded defence of the claims that our inferences really are guided by diverse explanatory considerations, and that this pattern of inference can take us towards the truth. This edition of Inference to the Best Explanation has also been updated throughout and includes a new bibliography.
Abductive Inference
This book is about abduction, 'the logic of Sherlock Holmes', and about how some kinds of abductive reasoning can be programmed in a computer. The work brings together Artificial Intelligence and philosophy of science and is rich with implications for other areas such as, psychology, medical informatics, and linguistics. It also has subtle implications for evidence evaluation in areas such as accident investigation, confirmation of scientific theories, law, diagnosis, and financial auditing. The book is about certainty and the logico-computational foundations of knowledge; it is about inference in perception, reasoning strategies, and building expert systems.
Self-inference Processes
First Published in 1990. Routledge is an imprint of Taylor & Francis, an informa company.
Inference and Understanding
A review of empirical and theoretical work on reasoning and linguistic inference, which will be a useful introduction to the subject for students of language and thought. The book focuses on the relationship between what people do and what people are supposed to do when making inferences.
The Structure of Scientific Inference
This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1974.
Causal Inference
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.
Inference, Consequence, and Meaning
Inferentialism as a theory of meaning builds on the idea that what a linguistic expression means depends exclusively on the inferential rules that govern its use. Following different strategies and exploring various case studies, the authors of this collection of essays discuss under what circumstances and to what extent the central tenets of inferentialism are tenable. The essays in this volume present the results of a three-year research project “Representation and Inference” which was conducted from the beginning of 2008 to the end 2010. The aim of the project was to assess the research program of inferentialism as it has been pursued recently by Robert Brandom, Mark Lance, and Jaroslav Peregrin. Earlier versions of these texts were presented at the conference “Inference, Consequence, and Meaning” held in Sofia on the 3rd and 4th of December, 2008.
Reading Between the Lines
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.
