Probabilistic Programming and Bayesian Methods for Hackers
by Cameron Davidson-Pilon
Publisher: GitHub, Inc. 2013
This book is designed as an introduction to Bayesian inference from a computational understanding-first, and mathematics-second, point of view. The book assumes no prior knowledge of Bayesian inference nor probabilistic programming.
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by Justin Solomon - CRC Press
Using examples from a broad base of computational tasks, including data processing and computational photography, the book introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into theoretical tools.
by Thomas Hales - arXiv
Computers have rapidly become so pervasive in mathematics that future generations may look back to this day as a golden dawn. The article gives a survey of mathematical proofs that rely on computer calculations and formal proofs.
by Philip J. Koopman, Jr. - Academic Press
The results of cache-simulation experiments with an abstract machine for reducing combinator graphs are presented. The abstract machine, called TIGRE, exhibits reduction rates that compare favorably with previously reported techniques.
by Bill Casselman - Cambridge University Press
The author gives an introduction to basic features of the PostScript language and shows how to use it for producing mathematical graphics. The book includes the discussion computer graphics and some comments on good style in mathematical illustration.