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Score Matching-based Pseudolikelihood Estimation of Neural Marked Spatio-Temporal Point Process with Uncertainty Quantification
Specifically, our framework adopts a normalization-free objective by estimating the pseudolikelihood of marked STPPs through score-matching and offers uncertainty quantification for the predicted event time, location and mark by computing confidence regions over the generated samples.
Pivotal Estimation of Linear Discriminant Analysis in High Dimensions
We consider the linear discriminant analysis problem in the high-dimensional settings.
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