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Found 2 papers, 1 papers with code
Nesting Particle Filters for Experimental Design in Dynamical Systems
In this paper, we propose a novel approach to Bayesian experimental design for non-exchangeable data that formulates it as risk-sensitive policy optimization.
Risk-Sensitive Stochastic Optimal Control as Rao-Blackwellized Markovian Score Climbing
Stochastic optimal control of dynamical systems is a crucial challenge in sequential decision-making.
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