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Applied Statistics III
Overview
Assignments
HW0: PyTorch Primer
HW1: Bayesian Linear Regression
HW2: Gibbs Sampling and Metropolis-Hastings
HW3: Continuous Latent Variable Models
HW4: Bayesian Mixture Models
HW5: Poisson Matrix Factorization
HW6: Neural Networks and VAEs
HW7: Autoregressive HMMs
HW8: Sigmoidal Gaussian Cox Processes
Notebooks
Bayesian Analysis of the Normal Distribution
The Multivariate Normal Distribution
Hierarchical Gaussian Models
Markov Chain Monte Carlo
Coordinate Ascent Variational Inference for GMMs
CAVI in a Simple Gaussian Model
Latent Dirichlet Allocation
Gradient-based VI in a Simple Gaussian Model
Neural Networks and VAEs
Gaussian Processes
References
References
.md
.pdf
References
References
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