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Creators/Authors contains: "Jiayu Zhai, Matthew Dobson"

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  1. (, Proceedings of Machine Learning Research)
    Joan Bruna, Jan S (Ed.)
    The time evolution of the probability distribution of a stochastic differential equation follows the Fokker-Planck equation, which usually has an unbounded, high-dimensional domain. Inspired by Li (2019), we propose a mesh-free Fokker-Planck solver, in which the solution to the Fokker-Planck equation is now represented by a neural network. The presence of the differential operator in the loss function improves the accuracy of the neural network representation and reduces the demand of data in the training process. Several high dimensional numerical examples are demonstrated. 
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    Accepted Manuscript Full Text Available