JSD for each model parameter with respect to the reference posteriors obtained using BXA. The JSD quantifies the similarity between posterior distributions. A smaller JSD indicates greater similarity. Below the dashed line, the posteriors are similar. We present the JSD values for three different dimension reduction techniques: PCA, spectral summaries, and the auto-encoder. Among these methods, the auto-encoder yields posteriors most similar to those from BXA. We also consider a case in which an embedding network, identical to the encoder component of the auto-encoder, is used to compress the spectra before passing them to the NDE. After applying importance sampling, the resulting posteriors closely match those from BXA. We also show the SIXSA posteriors corrected with the sampling importance sampling technique. They are also very close to the BXA reference posteriors. Finally, for the sake of the comparison, we include the posteriors computed using the XSPEC MCMC method.