Propose an alternative method for approximating the posterior probability distribution of user features, explaining the tradeoffs involved in your approach.

Use Hamiltonian (hybrid) Monte Carlo to directly sample from the non-diagonal Gaussian conditional. This provides a more efficient and stable way to compute posterior probabilities at the cost of increased computational overhead and potential mode collapse.