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Article summary:

1. DynaNet is a hybrid deep learning and time-varying state-space model that can be trained end-to-end.

2. The neural Kalman dynamical model allows for the exploitation of the relative merits of each approach, resulting in state-of-the-art estimation and prediction on physically challenging tasks.

3. DynaNet can indicate failures through investigation of properties such as the rate of innovation (Kalman Gain).

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