This document accompanies the book \Computer vision: models, learning, and inference" by Simon J.D. Prince. It contains concise descr iptions of almost all of the models and algorithms in the book. The goal is to provide sufficient information to im
Title Refining the Concept of Scientific Inference When Working with Big Data Author(s) Ben A. Wender, et al Publisher: National Academies Press (March 24, 2017) Hardcover/Paperback 114 Pages Book Descr iption The concept of utilizing big data to en
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 neurosci
Computer Vision Models, Learning, and Inference The goal of computer vision is to extract useful information from images. This has proved a surprisingly challenging task; it has occupied thousands of intelligent and creative minds over the last four
Imagine a world where computational simulations can be inverted as easily as running them forwards, where data can be used to refine models automatically, and where the only expertise one needs to carry out powerful statistical analysis is a basic p
The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chapters of slow, mathematical analysis. The typical text on Bayesian inference involves two to three chapters on probability theory, then enters what Bay
