Temporal Point Processes

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Overview

Temporal point processes describe event sequences through an intensity that specifies how likely an event is at each moment, often conditioned on past events and their marks. Classical Hawkes and renewal models capture self-excitation or recurring-event patterns, while neural intensity models, Transformers, neural ODEs, splines, Gaussian processes, and diffusion or flow methods add flexibility for complex temporal and spatiotemporal data. These models support next-event prediction, sequence generation, latent-intensity and network recovery, and applications ranging from healthcare and business logs to online activity and markets; evaluation commonly uses likelihood, timing and type accuracy, calibration, and synthetic stress tests. A key tension is balancing expressive models and scalable inference with interpretability, calibrated uncertainty, and reliable generalization when event histories are sparse or patterns shift.

Latest papers

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35 papers6 papers in the last four weeks, against 1 the four weeks before. 0.0% of all new papers.

  1. Exponential Wake-Up Overshoot in Explicit Gaussian Point-Process Filters

    Oct 25, 2026Hanwu Qin, Dianhai WangTemporal Point ProcessesBayesian Filtering

    Institute of Intelligent Transportation Systems, Zhejiang University, Hangzhou 310058, China

  2. Martingale Posterior Cox Processes

    Oct 17, 2026Joshua Rooijakkers, Edwin FongTemporal Point ProcessesBayesian Inference

    Imperial College London · University of Hong Kong

  3. Projected Wasserstein-Fisher-Rao Flows for Hawkes Background-Intensity Estimation

    Oct 14, 2026Isaias Banales, Arturo JaramilloHawkes ProcessesTemporal Point Processes

    Facultad de Ciencias, Universidad Aut´onoma de M´exico · Department of Probability and Statistics, Centro de Investigaci´on en Matem´aticas A.C., Guanajuato, M´exico

  4. Amortized Variational Inference of Latent Intensities from Replicated Point Patterns

    Oct 12, 2026Wenqing Liu, Xenia Miscouridou, Déborah SulemAmortized InferenceVariational Inference

    Faculty of Informatics, Università della Svizzera italiana, Lugano, Switzerland · Department of Mathematics and Statistics, University of Cyprus, Nicosia, Cyprus

  5. Exact Phase-Type Point Processes for Certified Measurement and Prediction of Event Streams

    Oct 10, 2026Sayak DuttaHawkes ProcessesTemporal Point Processes

  6. Modeling the Arrival Time of Information-Bearing Events in Natural Language

    Oct 9, 2026Leyi Lao, Yulin Ou, Yang Xu +1Event Time PredictionTemporal Point Processes

    Computational Linguistics and Consciousness Sciences Lab, Southern University of Science and Technology, Shenzhen, China

  7. Probabilistic Forecasting of Business Process Executions with Neural Temporal Point Processes

    Sep 18, 2026Jiaxin Yuan, Daniela Grigori, Han van der AaProbabilistic ForecastingPredictive Process Monitoring

    Paris Dauphine University-PSL, Pl. du Maréchal de Lattre de Tassigny, 75016 Paris, France · University of Vienna, Universitätsring 1, 1010 Wien, Austria

  8. Certifying What Helps Customer-Return Timing: A Screen-and-Confirm Test for Conditioning Signals, and Why Decay Is Nearly Enough

    Aug 12, 2026Sang Su Lee, Vineeth Loganathan, Shishir Dash +1Event Time PredictionTemporal Point Processes

    Thumbtack, Inc. San Francisco, CA, USA

  9. Smooth Neural Point Processes via B-Splines

    Jul 23, 2026Michele Bellomo, Riccardo Ramaschi, Alberto Dolara +1Temporal Point Processes

    Politecnico di Milano Milan, Italy · University College London London, UK

  10. ReDiTT: Retrieval Augmented Conditional Diffusion Transformers for Asynchronous Time Series

    Jul 14, 2026Saiyue Lyu, Zhitian Zhang, Ruizhi Deng +1Irregular Time-Series ModelingEvent Time Prediction

    Department of Computer Science, University of British Columbia · Work done during an internship at RBC Borealis. · RBC Borealis

  11. NeuroMem-FHP: A Likelihood-Free Deep Learning Framework for Parameter Estimation of Fractional Hawkes Process

    Jul 13, 2026Neha Gupta, Aditya MaheshwariTemporal Point ProcessesParameter Estimation

    Operations Management and Quantitative Techniques Area, Indian Institute of Management Indore, Indore 453556, India.

  12. From Jumps to Signatures: a Generative Method for Temporal Point Processes

    Jul 7, 2026Niels Cariou-Kotlarek, Vasileios LamposTemporal Point ProcessesGenerative Modeling

    Centre for Artificial Intelligence Department of Computer Science University College London

  13. Unsupervised Anomaly Detection of Information Operations Users via Behavioral and Language Patterns

    Jul 7, 2026Sishun Liu, Sajal Halder, Ke Deng +2Social Media AnalysisTemporal Point Processes

    RMIT University, Melbourne, Victoria 3000, Australia · Macquarie University, Sydney, New South Wales 2000, Australia

  14. Efficient Temporal Point Processes via Monotone Alternating Splines

    Jul 2, 2026Cheng Wan, Quyu Kong, Feng ZhouTemporal Point Processes

    Hong Kong University of Science and Technology, Hong Kong · Alibaba Cloud, Hangzhou, China · Center for Applied Statistics and School of Statistics, Renmin University of China, Beijing, China

  15. When Context Compensates for Sparse Event History: AlphaEarth for Spatio-Temporal Point-Process Forecasting

    Jul 1, 2026Yahya Aalaila, Mouad Elhamdi, Gerrit Großmann +3Temporal Point ProcessesSpatial Generalization

    1German Research Center for Artificial Intelligence (DFKI) · 5Rhineland-Palatinate Technical University of Kaiserslautern-Landau (RPTU) · 2Universit´e Mohammed VI Polytechnique +2

  16. Seahorse: A Unified Benchmarking Framework for Spatiotemporal Event Modeling

    Jul 1, 2026Yahya Aalaila, Gerrit Großmann, Sebastian VollmerTemporal Point Processes

    German Research Center for Artificial Intelligence (DFKI), Data Science and its Applications Research Group, Kaiserslautern, Germany · Department of Computer Science, Rhineland-Palatinate Technical University of Kaiserslautern-Landau (RPTU), Kaiserslautern, Germany

  17. Latent Block-Diffusion Temporal Point Processes: A Semi-Autoregressive Framework for Asynchronous Event Sequence Generation

    Jun 23, 2026Shuai Zhang, Yancheng Chen, Chuan Zhou +5Temporal Point ProcessesLatent Diffusion Models

    Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China · Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China · Department of Data Science, City University of Hong Kong, Hong Kong 999077, China +1

  18. HawkesNest: A Multi-Axis Synthetic Benchmark for Spatiotemporal Pattern Complexity

    Jun 15, 2026Yahya Aalaila, Sumantrak Mukherjee, Gerrit Großmann +1Temporal Point ProcessesSynthetic Benchmark Generation

    German Research Center for Artificial Intelligence (DFKI), Data Science and its Applications Research Group, Kaiserslautern, Germany

  19. Non-Negative Matrix Factorization for Event Data

    Jun 4, 2026Raphaël RomeroTemporal Point ProcessesLatent Variable Models

    Ghent University · Ghent, Belgium

  20. GLIDE: Graph-guided Leap Inference for Diffusion Estimation of Spatio-Temporal Point Processes

    May 31, 2026Guanyu Zhou, Yao Liu, Yanglei Gan +5Event Time PredictionTemporal Point Processes

    University of Electronic Science and Technology of China, Chengdu, China

  21. Structured Neural Marked Point Processes for Interpretable Event Interaction Modeling

    May 17, 2026Zhitong Xu, Qiwei Yuan, Yinghao Chen +2Temporal Point ProcessesNeural Network Interpretability

    Kahlert School of Computing, University of Utah · Celonis AI

  22. SurF: A Generative Model for Multivariate Irregular Time Series Forecasting

    May 13, 2026Mohammad R. Rezaei, Tejas Balaji, Rahul G. KrishnanIrregular Time-Series ModelingMultivariate Time Series Forecasting

    Department of Computer Science University of Toronto Vector Institute Toronto, ON, Canada

  23. On Observation Time for Recovering Latent Hawkes Networks

    May 8, 2026Jonas Linkerhägner, Michele Bortolasi, Lorenzo Baldassari +2Temporal Point ProcessesSample Complexity

    University of Basel · Rice University

  24. Arbitrarily Conditioned Hierarchical Flows for Spatiotemporal Events

    May 2, 2026Keyan Chen, Qiwei Yuan, Zhitong Xu +2Temporal Point ProcessesFlow Matching

    Kahlert School of Computing University of Utah · Celonis AI

  25. Towards Event-Aware Forecasting in DeFi: Insights from On-chain Automated Market Maker Protocols

    Apr 22, 2026Huaiyu Jia, Jiehshun You, Yizhi Luo +2Event Time PredictionTemporal Point Processes

    HKUST(GZ) · GUANGZHOU, China · Hong Kong Polytechnic University +1

  26. Modeling Patient Care Trajectories with Transformer Hawkes Processes

    Apr 7, 2026Saumya Pandey, Varun ChandolaTrajectory PredictionLongitudinal EHR Modeling

    Computational and Data-Enabled Sciences, University at Buffalo, Buffalo, USA · Department of Computer Science and Engineering, University at Buffalo, Buffalo, USA

  27. Massively Parallel Exact Inference for Hawkes Processes

    Apr 1, 2026Ahmer Raza, Hudson SmithHawkes ProcessesTemporal Point Processes

    Clemson University

  28. Kronecker-Structured Nonparametric Spatiotemporal Point Processes

    Mar 24, 2026Zhitong Xu, Qiwei Yuan, Yinghao Chen +3Temporal Point Processes

    Kahlert School of Computing, The University of Utah · College of Arts & Sciences, Utah State University · Celonis AI

  29. Bridging Discrete Marks and Continuous Dynamics: Dual-Path Cross-Interaction for Marked Temporal Point Processes

    Mar 12, 2026Yuxiang Liu, Qiao Liu, Tong Luo +3Temporal Point Processes

    University of Electronic Science and Technology of China, Chengdu, Sichuan, China

  30. A Learning-Based Superposition Operator for Non-Renewal Arrival Processes in Queueing Networks

    Mar 11, 2026Eliran SherzerQueueing TheoryTemporal Point Processes

    Industrial Engineering, Ariel University, Ramat HaGolan St 65, Ariel, 4070000, Israel.