THE PLATELET CONCENTRATES THERAPY: FROM THE BIASED PAST TO THE ANTICIPATED FUTURE


Interferometric Phase Reconstruction Based on Probability Generative Model: Toward Efficient Analysis of High-Dimensional SAR Stacks

In order to minimize the influence of decorrelation noise on multi-temporal interferometric synthetic aperture radar (MT-InSAR) applications, a series of phase reconstruction methods have been proposed in recent years.Unfortunately, current phase reconstruction methods generally exhibit a low computational efficiency due to their high non-linearity

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Graph Neural Networks for Maximum Constraint Satisfaction

Many combinatorial optimization problems can be phrased in the language of constraint satisfaction problems.We introduce a graph neural network architecture for solving such optimization problems.The architecture is generic; it works for all binary constraint satisfaction problems.Training is unsupervised, and it is sufficient to train on relativel

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