Resources đ
- 2021-05-12-information-theory - my post on Information Theory (also on the blog)
- Anatomize Deep Learning with Information Theory LilâLog
- Information Theory and Statistics by John Duchi ([Notes]({% link files/John-Duchi-Statistics-311-Electrical-Engineering-377.pdf %}))
- Information Theory, Inference, and Learning Algorithms: Home by David MacKay
- Statistical Mechanics by Matthew D. Schwartz
- Information Theory andNetwork Coding by Raymond W. Yeung
- A First Course in Information Theory by Raymond W. Yeung
- Information, Physics, and Computation by Marc MĂ©zard and Andrea Montanari
- Small Summaries for Big Data by Graham Cormode and Ke Yi
- Information Theory and Statistics an overview
- Constraint satisfaction networks in Physics and Computation: Probabilistic approaches (2006) by Marc MĂ©zard and Andrea Montanari - chapter 1, 2, 4 and 6
- Entropy and Information Theory First Edition, Corrected (June 26, 2023) by Robert M. Gray
Books available in Library
- Gray (2013) Entropy and Information Theory 1st Edition Corrected.pdf
- Cover and Thomas (2006) Elements Of Information Theory.pdf
- Mezard and Montanari (2009) Information, Physics and Computation (Parts A-F)
- Yeung (2001) A First Course in Information Theory.pdf
- Yeung ANNOTATED (2007) Information Theory and Network Coding.pdf
- Yeung (2007) Information Theory and Network Coding.pdf
- Duchi (2019) Information Theory and Statistics Notes for Stanford Statistics 311 Electrical Engineering 377 .pdf
- MacKay (2003) Information Theory, Inference and Learning Algorithms.pdf
- Gray (2013) Entropy and Information Theory.pdf
- MacKay David (2003) Information Theory, Inference and Learning Algorithms.pdf