Gibbs Sampling: This algorithm updates each parameter in turn, conditioning on the current values of the other parameters. Metropolis-Hastings: This algorithm proposes new parameter values and accepts or rejects them based on a certain acceptance criterion. Hamiltonian Monte Carlo (HMC): This algorithm uses gradients to explore the parameter space more efficiently.