Implementation of "Detecting Anomalous Event Sequences with Temporal Point Processes" (NeurIPS 2021)
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Updated
Dec 30, 2021 - Jupyter Notebook
Implementation of "Detecting Anomalous Event Sequences with Temporal Point Processes" (NeurIPS 2021)
Code and real data for "Counterfactual Temporal Point Processes", NeurIPS 2022
Implementation of "Neural Jump-Diffusion Temporal Point Processes" (ICML 2024 Spotlight)
This repository contains recent background materials, current works, and codes for researching in TPP.
PyTorch-Lightning implementation of Meta Temporal Point Processes
The official Pytorch implementation of paper "Patent Citation Dynamics Modeling via Multi-Attention Recurrent Networks""
Implementation of "Conformal Anomaly Detection in Event Sequences" (ICML 2025)
Master thesis title: "Towards Event Sequence Foundation Models: exploring temporal point process transformers for power grid fault prediction" Dataset and modelling infrastructure for modelling "event streams": sequences of continuous time, multivariate events with complex internal dependencies.
Dual Network Hawkes Process -- Analyzing Topic Transitions in Text-Based Social Cascades
Implementation of "Multiple Hypothesis Testing for Anomaly Detection in Multi-type Event Sequences" (ICDM 2023)
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