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Research questionHow can PAC-Bayesian reconstruction guarantees for variational autoencoders handle temporal dependence in time-series data?Variational autoencoders for time series operate on dependent observations, so guarantees derived for i.i.d. samples do not directly describe their reconstruction behavior. The challenge is to characterize generalization under temporal latent structure without having guarantees deteriorate simply because trajectories are long.
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Statistical Machine Learning
Latest papersRecent research connected to this question, newest first.PAC-Bayesian Reconstruction Guarantees for Time Series Variational AutoencodersThe source concerns PAC-Bayesian reconstruction bounds for variational autoencoders with Markovian latent structures and sequential generative processes. It reports guarantees whose bounds do not grow with trajectory length, under assumptions described as common in the literature, and gives an example framework for verifying those assumptions.research paper · Sep 4, 2026
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