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HyperHawkes: Hypernetwork based Neural Temporal Point Process
We also develop a hypernetwork based continually learning temporal point process for continuous modeling of time-to-event sequences with minimal forgetting.
Bayesian Neural Hawkes Process for Event Uncertainty Prediction
Therefore, we propose a novel point process model, Bayesian Neural Hawkes process (BNHP) which leverages uncertainty modelling capability of Bayesian models and generalization capability of the neural networks to model event occurrence times.
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