Prediction Under Uncertainty with Error Encoding Networks

arXiv: Artificial Intelligence, 2018.

Cited by: 2|Views155

Abstract:

In this work we introduce a new framework for performing temporal predictions in the presence of uncertainty. It is based on a simple idea of disentangling com- ponents of the future state which are predictable from those which are inherently unpredictable, and encoding the unpredictable components into a low-dimensional latent variable w...More

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