On Learning Heteroscedastic Noise Models within Differentiable Bayes Filters

In many robotic applications, it is crucial to maintain a belief about the state of a system, like the location of a robot or the pose of an object. These state estimates serve as input for planning and decision making and provide feedback during task execution... (read more)

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