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Found 2 papers, 1 papers with code
Explainable History Distillation by Marked Temporal Point Process
To efficiently solve \acrshort{ehd}, we rewrite the task into a \gls{01ip} and directly estimate the solution to the program by a model called \acrfull{model}.
Intensity-free Integral-based Learning of Marked Temporal Point Processes
In the marked temporal point processes (MTPP), a core problem is to parameterize the conditional joint PDF (probability distribution function) $p^*(m, t)$ for inter-event time $t$ and mark $m$, conditioned on the history.
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