A differentiable particle filter with L1 proximal updates estimates sparse polynomial transition functions and interaction graphs for nonlinear state-space models.
Learning a sparse polynomial approximation to the transition function of general state-space models,
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GraphGrad: Efficient Estimation of Sparse Polynomial Representations for General State-Space Models
A differentiable particle filter with L1 proximal updates estimates sparse polynomial transition functions and interaction graphs for nonlinear state-space models.