A Neural Implementation of the Kalman Filter

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The limits and potentials of deep learning for robotics (2018, background): “…re-composition of component solutions from different places on the spectrum can be achieved with differentiable versions of existing algorithms (one end of the spectrum) that are compatible solutions obtained with back-propagation (other end of the spectrum) [16], [39], [50], [108], [116], [128].”
Backprop KF: Learning Discriminative Deterministic State Estimators (2016, background): “The use of recurrent neural networks (RNNs) for state estimation has been explored in several prior works [24, 4, 23, 19], but has generally been limited to simple tasks without complex sensory inputs such as images.”