Schedule and Syllabus

Week Date (Mon) Monday Lecture Wednesday Lecture Lab on Friday HW
W1 Sep 3 HOLIDAY Probability, Conditionals, distributions, and Entropy, KL? Math, Stats Refresher, Gaussian distrib, algebra and matrix calculus HW1
           
W2 Sep 10 Sampling, Expectations, LLN, CLT, LOTUS, and Monte Carlo, inverse transform Frequentist MLE and sampling, Bootstrap, Binomial distribution, MLE for regression, regression eg poisson-gamma MLE, freq stats. HW2
           
W3 Sep 17 Bayesian Stats with conjugate priors, normal regularization, beta-binomial Rejection Sampling, Box Mueller, Importance Sampling Conjugate examples: poisson, binomial HW3
           
W4 Sep 24 Regression, predictive distribution, bias-variance tradeoff, regularization. Bayesian regression? Loss functions, Information theory, KL-Divergence and Deviance, Bayes risk, AIC Sine curve regression, confidence intervals, credible intervals? HW4
           
W5 Oct 1 Logistic MLE, Generative counterpart, Classification, Bayes risk, GD, SGD, supervised->unsupervized More SGD, MLP regression and classification PyTorch and ANN HW5
           
W6 Oct 8 HOLIDAY Mixtures, EM, Gaussian Mixture models EM HW6
           
W7 Oct 15 Hierarchical Models, intractable posteriors, empirical bayes, grid, laplace, need for MCMC Markov chains, metropolis, theory discrete sampling, markov chains HW7
           
W8 Oct 22 Metropolis hastings, gibbs, sample checks Data Augmentation, HMC By Hand Gibbs for tumors, sample checks HW8:
           
W9 Oct 29 Exploring HMC, HMC tuning, NUTS. Sample checks, Energy, Divergence, model problems, ppc, credible intervals pymc3, coal disasters, bioassay HW9:
           
W10 Nov 5 ppc, wrapping into bayesian workflow, viz, SBC Bayesian regression, regression priors and issues, poisson glm Gelman Schools HW10:
           
W11 Nov 12 Overdispersion, Correlations, model comparison Model Comparison oceanic contd. Model selection, averaging prosocial chimps HW11:
           
W12 Nov 19 Variational, ADVI HOLIDAY HOLIDAY  
           
W13 Nov 26 Variational Inference, how good, VSBC? Gaussian Processes Mixture MCMC, variational Paper Due Friday
           
W14 Dec 3 Simulated Annealing and temperature as a tool Generative Modeling, Advanced Topics Lab, Odds and ends, and conclusion None
           
W15 Dec 10 Conclusion Lecture, READING PERIOD EXAM PERIOD EXAM PERIOD  
           
W16 Dec 17 EXAM PERIOD EXAM PERIOD (Exam Due)    
           
W17          

Notes: