Mladen Nikolić

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Dynamics of many real-world systems are naturally modeled by structured regression of representationally powerful Gaussian conditional random fields (GCRF) on evolving graphs. However, applications are limited to small and sparse evolving graphs due to high computational cost of the GCRF learning and inference. In this study, a new method is proposed to(More)
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