<ul><li>Temporal point process is commonly used to model asynchronous event sequences featuring occurrence timestamps.</li><li>Deep neural networks are emerging as a promising choice for capturing patterns in temporal point process.</li><li>This paper reviews recent research emphasis and difficulties in modeling asynchronous event sequences with deep temporal point process.</li><li>The study introduces recently proposed models and experiments to evaluate their performance.</li></ul>

An Empirical Study: Extensive Deep Temporal Point Process

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