Bayesian Methods

Bayesian Learning

Auto-Encoding Variational Bayes

• paper: http://arxiv.org/abs/1312.6114
• github: https://github.com/stitchfix/fauxtograph
• github: https://github.com/fchollet/keras/blob/master/examples/variational_autoencoder.py

Practical Bayesian Optimization of Machine Learning Algorithms

• paper: http://arxiv.org/abs/1206.2944v2
• github: https://github.com/JasperSnoek/spearmint
• github: https://github.com/HIPS/Spearmint

Bayesian Face Revisited: A Joint Formulation

• intro: ECCV 2012
• paper: http://research.microsoft.com/en-us/um/people/jiansun/papers/ECCV12_BayesianFace.pdf
• github: https://github.com/MaoXu/Joint_Bayesian/
• github: https://github.com/cyh24/Joint-Bayesian

UAI 2015 Amsterdam Tutorial: Optimal Algorithms for Learning Bayesian Network Structures

• video: https://www.youtube.com/watch?v=__JD3ptBR-w&hd=1
• video: http://pan.baidu.com/s/1ntEf4lr
• slides: http://auai.org/uai2015/proceedings/slides/UAI2015_LearningBN_PartI.pdf
• slides: http://auai.org/uai2015/proceedings/slides/UAI2015_LearningBN_PartII.pdf

Bayesian Learning

https://github.com/ReactiveCJ/BayesianLearning

Bayesian Methods of Parameter Estimation

• paper: http://homepages.inf.ed.ac.uk/rbf/CVonline/LOCAL_COPIES/AV0809/eshky.pdf

A Tutorial on Bayesian Belief Networks

• intro: 2001
• paper: http://dspace.dsto.defence.gov.au/dspace/bitstream/1947/3537/1/DSTO-TN-0403.pdf
• paper: http://pan.baidu.com/s/1eQNtUxW

A Tutorial on Learning With Bayesian Networks

• page: http://research.microsoft.com/apps/pubs/default.aspx?id=69588
• paper: http://research.microsoft.com/pubs/69588/tr-95-06.pdf

An Introduction to Bayesian Networks: Concepts and Learning from Data

• slides: http://nlp.postech.ac.kr/Course/CS704/LectureNotes/BayesianNetworks.pdf

Taking the Human Out of the Loop: A Review of Bayesian Optimization

• paper: http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7352306

Bayesian Optimization for Machine Learning : A Practical Guidebook

• intro: SigOpt
• arxiv: https://arxiv.org/abs/1612.04858
• homepage: https://sigopt.com/
• github: https://github.com/sigopt

Probabilistic Programming

Probabilistic Programming in Python

• slides: http://www.slideshare.net/PeadarCoyle/probabilistic-programming-in-python?qid=5982ead9-5606-4ef8-9faa-5d1782f34702&v=qf1
• slides: http://pan.baidu.com/s/1gdP0O8N

Reading List for MIT Probabilistic Computing Project

http://probcomp.csail.mit.edu/readings/

Lightweight Implementations of Probabilistic Programming Languages Via Transformational Compilation

• paper: http://web.stanford.edu/~ngoodman/papers/lightweight-mcmc-aistats2011.pdf
• talk: http://videolectures.net/aistats2011_wingate_lightweight/
• github: (“probabilistic-js”): https://github.com/dritchie/probabilistic-js

Introduction to Probabilistic Programming

• blog: http://austinrochford.com/resources/talks/dataphilly-jul2016.slides.html

webppl: Probabilistic programming for the web

• intro: webppl is a small but feature-rich probabilistic programming language embedded in Javascript.
• homepage: http://webppl.org/
• github: https://github.com/probmods/webppl

Probabilistic Data Analysis with Probabilistic Programming

• intro: MIT
• arxiv: http://arxiv.org/abs/1608.05347

The Design and Implementation of Probabilistic Programming Languages

• book: http://dippl.org/

Model-Based Machine Learning and Probabilistic Programming in RStan

• blog: https://blog.dominodatalab.com/video-model-based-machine-learning-webcast/

Deep Probabilistic Programming

• intro: Columbia University & Adobe Research & Google Research & Google Brain
• arxiv: https://arxiv.org/abs/1701.03757
• homepage: http://edwardlib.org/
• zoo: http://edwardlib.org/zoo
• code: http://edwardlib.org/iclr2017

The Algorithms Behind Probabilistic Programming

http://blog.fastforwardlabs.com/2017/01/30/the-algorithms-behind-probabilistic-programming.html

Edward: A library for probabilistic modeling, inference, and criticism.

• intro: A library for probabilistic modeling, inference, and criticism. Deep generative models, variational inference. Runs on TensorFlow.
• homepage: http://edwardlib.org/
• github: https://github.com/blei-lab/edward

Books

Probabilistic Programming & Bayesian Methods for Hackers

• homepage: http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/
• github: https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

Blogs

Let’s Learn: Probabilistic Programming

• part 1: https://medium.com/@Algomancer/lets-learn-about-probabilistic-programming-part-1-7988d6501e53#.dzjdiexu5
• part 2: https://medium.com/@Algomancer/let-s-learn-probabilistic-programming-part-2-c208f79f1dc1#.6hq2zzb7l

Bayesian Optimization of Machine Learning Models

http://blog.revolutionanalytics.com/2016/06/bayesian-optimization-of-machine-learning-models.html

Probabilistic Programming - Part 1

http://javaagile.blogspot.kr/2016/09/probabilistic-programming-part-1.html