Multiple Imputation with 'MIDAS2' Denoising Autoencoders // Fits 'MIDAS' denoising autoencoder models for multiple imputation of missing data, generates multiply-imputed datasets, computes imputation means, and runs Rubin's rules regression analysis. Wraps the 'MIDAS2' 'Python' engine via a local 'FastAPI' server over 'HTTP', so no 'reticulate' dependency is needed at runtime. Methods are described in Lall and Robinson (2022) doi:10.1017/pan.2020.49 and Lall and Robinson (2023) doi:10.18637/jss.v107.i09.