- hw1: Ancestral, Gibbs, Rejection sampling with discrete distributions
- hw2: FOPPL
evaluate
function in Pytorch on Gaussian Unknown Mean, Bayesian Regression, Hidden Markov, Bayesian Neural Net - hw3: Importance Sampling, Metropolis in Gibbs, Hamiltonian Monte Carlo in FOPPL
- hw4: Black Box Variational Inference in FOPPL
- hw5: HOPPL 'evaluate' function
- hw6: Sequential Monte Carlo in FOPPL on Gaussian Marsaglia, Hidden Markov