NOTE:
Homeworks are posted on the date they are assigned.
Readings are posted for the date they are due.

Date Topics Reading Homework
Week 1
Tu 1/8 Introduction   HW0, Due Tu 1/22
hw0.tex
LaTeX template for HW0 write-up
Th 1/10 Probability Crash Course    
Week 2
Tu 1/15 Probability Crash Course, cont. Albert, Ch 1  
Th 1/17 Maximum Likelihood Estimation Wikipedia: MLE  
Week 3
Tu 1/22 Intro to Bayesian Analysis Albert, Ch 2 HW0 Due (11:59 PM)
Th 1/24 Conjugate Priors
BernoulliBetaPrior.r		 Wikipedia: Conjugate Prior
Albert, Ch 3		 Reading Questions 1 Due
Week 4
Tu 1/29 Exponential Families   HW1, Due Tue 2/12
hw1.tex
Th 1/31 Maximum Entropy Priors Jaynes, 1968  
Week 5
Tu 2/5 Jeffreys' Prior
GaussianVariancePriors.r		 Wikipedia: Jeffreys Prior  
Th 2/7 Multiparameter Models Wikipedia: Prior for Mean & Variance of a Gaussian
Albert, Ch 4		 Reading Questions 2 Due
Week 6
Tu 2/12 Bayesian Linear Regression
BayesianLinearRegression.r		   HW1 Due (11:59PM)
Th 2/14 Graphical Models/Bayesian Networks Bishop, Ch 8.1-8.2 HW2, Due Tu 2/26 and Th 3/7
Week 7
Tu 2/19 Factor Graphs and Inference Bishop, Ch 8.4  
Th 2/21 Markov Random Fields Bishop, Ch 8.3  
Week 8
Tu 2/26 Introduction to Monte Carlo Methods
MonteCarlo.r		   HW2 Partial Code Due
Th 2/28 Variance Reduction, Importance Sampling
VarianceReduction.r		    
Week 9
Tu 3/5 Markov Chain Monte Carlo    
Th 3/7 Metropolis-Hastings Algorithm   Completed HW2 Due
Week 10
Tu 3/12 Spring Break - No Class    
Th 3/14 Spring Break - No Class    
Week 11
Tu 3/19 Gibbs Sampling    
Th 3/21 Hamiltonian Monte Carlo    
Week 12
Tu 3/26      
Th 3/28      
Week 13
Tu 4/2      
Th 4/4      
Week 14
Tu 4/9      
Th 4/11      
Week 15
Tu 4/16      
Th 4/18      
Week 16
Tu 4/23      
Classes End