Score Kalman Filter performs nonlinear moment-based filtering by reducing density fitting to a linear solve from moments via score matching and closing hierarchies with Stein's identity, avoiding partition function integrals entirely.
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A novel Sum-of-Squares form for conditional density estimation in Markov processes enables analytical belief propagation with exact constraint adherence and better scaling than prior methods.
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The Score Kalman Filter
Score Kalman Filter performs nonlinear moment-based filtering by reducing density fitting to a linear solve from moments via score matching and closing hierarchies with Stein's identity, avoiding partition function integrals entirely.
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Learning Markov Processes as Sum-of-Square Forms for Analytical Belief Propagation
A novel Sum-of-Squares form for conditional density estimation in Markov processes enables analytical belief propagation with exact constraint adherence and better scaling than prior methods.