└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Gaussian Processes - A List of References 2 | I am providing a list of references for Gaussain Processes. 3 | 4 | ## Books and Book Chapters 5 | 1. **Gaussian Processes for Machine Learning** by Carl Edward Rasmussen and Christopher K. I. Williams published by The MIT Press. http://www.gaussianprocess.org/gpml/ and [pdf] http://www.gaussianprocess.org/gpml/chapters/RW.pdf. 6 | 7 | This is the ultimate referece for Gaussian Processes. The book introduces Gaussian Processes, comprehensively covers regression and classfication with Gaussian processes and describes in detail related topics including covariacne funcions (i.e., kernels), hyperparamters, approximations and much more. I will strongly recommend this book for any one interested in learn about Gaussian Processes and using these in their machine learning work. 8 | 9 | 10 | 2. **Machine Learning A Probabilistic Perspective (Chapter 15)** by Kevin P. Murphy published by The MIT Press. https://mitpress.mit.edu/books/machine-learning-1 and https://www.cs.ubc.ca/~murphyk/MLbook/. 11 | 12 | 3. **Pattern Recognition and Machine Learning (Section 6.4)** by Christopher M. Bishop. https://www.springer.com/us/book/9780387310732 and https://www.microsoft.com/en-us/research/people/cmbishop/#!prml-book 13 | 14 | 4. **Information Theory, Inference and Learning Algorithms (Chapter 45)** by David J. C. MacKay. Links: Book http://www.inference.org.uk/mackay/itprnn/ps/534.548.pdf. 15 | 16 | 5. **Bayesian Reasoning and Machine Learning (Chapter 19)** by David Barber. http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/091117.pdf. 17 | 18 | ## Courses and Notes 19 | 1. **CS281: Advanced Machine Learning (Lecture 19)** Links https://www.seas.harvard.edu/courses/cs281/. 20 | 21 | 2. **CS229: Machine Learning**. http://cs229.stanford.edu/section/cs229-gaussian_processes.pdf 22 | 23 | 24 | ## Peer-reviewed and non-peer reviewed resources 25 | 1. **Gaussian Processes: A Quick Introduction** by Mark Ebden. https://arxiv.org/abs/1505.02965 26 | 2. **Gaussian Processes for Dummies** by Katherine Bailey. http://katbailey.github.io/post/gaussian-processes-for-dummies/ 27 | 3. **Gaussian processes** by Martin Krasser. http://krasserm.github.io/2018/03/19/gaussian-processes/ 28 | 4. **Fitting Gaussian Process Models in Python** by Chris Fonnesbeck. https://blog.dominodatalab.com/fitting-gaussian-process-models-python/ 29 | --------------------------------------------------------------------------------