Showing 2025Show all
2 papers · 1 filter
cs.LG2025
Addressing Mark Imbalance in Integration-free Neural Marked Temporal Point Processes
Sishun Liu, Ke Deng, Yongli Ren +2
Marked Temporal Point Process (MTPP) has been well studied to model the event distribution in marked event streams, which can be used to predict the mark and arrival time of the ne…
cs.LG2025
Learning Marked Temporal Point Process Explanations based on Counterfactual and Factual Reasoning
Sishun Liu, Ke Deng, Xiuzhen Zhang +1
Neural network-based Marked Temporal Point Process (MTPP) models have been widely adopted to model event sequences in high-stakes applications, raising concerns about the trustwort…