%2C%20which%20are%20capable%20of%20substantially%20reducing%20the%20volume%20of%20transmitted%20data%20while%20guaranteeing%20secure%20lossy%20image%20reconstruction.%20CVAEs%20have%20been%20demonstrated%20to%20outperform%20conventional%20compression%20methods%20such%20as%20JPEG2000%20by%20a%20substantial%20margin%20on%20compression%20benchmark%20datasets.%20The%20proposed%20model%20draws%20on%20the%20strength%20of%20the%20CVAEs%20capability%20to%20abstract%20data%20into%20highly%20insightful%20latent%20spaces%2C%20and%20combining%20it%20with%20the%20utilization%20of%20an%20entropy%20bottleneck%20is%20capable%20of%20finding%20an%20optimal%20balance%20between%20compressibility%20and%20reconstruction%20quality.%20The%20balance%20is%20reached%20by%20optimizing%20over%20a%20composite%20loss%20function%20that%20represents%20the%20rate-distortion%20curve.)
%20when%20the%20training%20data%20is%20incomplete.%20We%20show%20that%20missing%20data%20increases%20the%20complexity%20of%20the%20model's%20posterior%20distribution%20over%20the%20latent%20variables%20compared%20to%20the%20fully-observed%20case.%20The%20increased%20complexity%20may%20adversely%20affect%20the%20fit%20of%20the%20model%20due%20to%20a%20mismatch%20between%20the%20variational%20and%20model%20posterior%20distributions.%20We%20introduce%20two%20strategies%20based%20on%20(i)%20finite%20variational-mixture%20and%20(ii)%20imputation-based%20variational-mixture%20distributions%20to%20address%20the%20increased%20posterior%20complexity.%20Through%20a%20comprehensive%20evaluation%20of%20the%20proposed%20approaches%2C%20we%20show%20that%20variational%20mixtures%20are%20effective%20at%20improving%20the%20accuracy%20of%20VAE%20estimation%20from%20incomplete%20data.)
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