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The class of continuous time Bayesian network classifiers is defined; it solves the problem of supervised classification on multivariate trajectories evolving in continuous time. The trajectory consists of the values of discrete attributes that are measured in continuous time, while the predicted class is expected to occur in the future. Two instances from(More)
The functional variable method is a powerful mathematical tool for obtaining exact solutions of nonlinear evolution equations in mathematical physics. In this paper, the functional variable method is used to establish exact solutions of the (2+1)-dimensional Kadomtsov-Petviashivilli-Benjamin-Bona-Mahony (KP-BBM) equation, the (2+1)-dimensional(More)
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