Uncertainty in Neural Relational Inference Trajectory Reconstruction

24 Jun 2020Vasileios KaraviasBen DayPietro Liò

Neural networks used for multi-interaction trajectory reconstruction lack the ability to estimate the uncertainty in their outputs, which would be useful to better analyse and understand the systems they model. In this paper we extend the Factorised Neural Relational Inference model to output both a mean and a standard deviation for each component of the phase space vector, which together with an appropriate loss function, can account for uncertainty... (read more)

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