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.
Beliefs are shown with corresponding Monte Carlo ground truth below
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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.