Lifted Relational Kalman Filtering

  title={Lifted Relational Kalman Filtering},
  author={Jaesik Choi and Abner Guzm{\'a}n-Rivera and Eyal Amir},
Kalman Filtering is a computational tool with widespread applications in robotics, financial and weather forecasting, environmental engineering and defense. Given observation and state transition models, the Kalman Filter (KF) recursively estimates the state variables of a dynamic system. However, the KF requires a cubic time matrix inversion operation at every timestep which prevents its application in domains with large numbers of state variables. We propose Relational Gaussian Models to… CONTINUE READING
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