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cs.LG2023
Explainable History Distillation by Marked Temporal Point Process
Sishun Liu, Ke Deng, Yan Wang +1
Explainability of machine learning models is mandatory when researchers introduce these commonly believed black boxes to real-world tasks, especially high-stakes ones. In this pape…
cs.LG2023
Intensity-free Integral-based Learning of Marked Temporal Point Processes
Sishun Liu, Ke Deng, Xiuzhen Zhang +1
In the marked temporal point processes (MTPP), a core problem is to parameterize the conditional joint PDF (probability distribution function) for inter-event time a…