mlsanityData to 7 Oct 2026

Uncovering Causality from Multivariate Hawkes Integrated Cumulants

arXiv 1607.06333 ↗First posted 21 Jul 2016stat.ML cs.LGcited by 38

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Abstract (arXiv)

We design a new nonparametric method that allows one to estimate the matrix of integrated kernels of a multivariate Hawkes process. This matrix not only encodes the mutual influences of each nodes of the process, but also disentangles the causality relationships between them. Our approach is the first that leads to an estimation of this matrix without any parametric modeling and estimation of the kernels themselves. A consequence is that it can give an estimation of causality relationships between nodes (or users), based on their activity timestamps (on a social network for instance), without knowing or estimating the shape of the activities lifetime. For that purpose, we introduce a moment matching method that fits the third-order integrated cumulants of the process. We show on numerical experiments that our approach is indeed very robust to the shape of the kernels, and gives appealing results on the MemeTracker database.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). First posted on arXiv 21 Jul 2016.

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Citing papers per year: 2021: 7; 2022: 3; 2023: 12; 2024: 7; 2025: 6; 2026: 3.

38 papers.

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  1. 2021Neural Temporal Point Processes: A Reviewcited by 113
  2. 2023Causal Discovery from Temporal Data: An Overview and New Perspectivescited by 43
  3. 2021Counterfactual Temporal Point Processescited by 20
  4. 2021THP: Topological Hawkes Processes for Learning Causal Structure on Event Sequencescited by 19
  5. 2022Cardinality-Regularized Hawkes-Granger Modelcited by 14
  6. 2023Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequencescited by 14
  7. 2021Mitigating Performance Saturation in Neural Marked Point Processes: Architectures and Loss Functionscited by 12
  8. 2022Causal Discovery in Hawkes Processes by Minimum Description Lengthcited by 11
  9. 2021Sequential change-point detection for mutually exciting point processes over networkscited by 7
  10. 2022Nonparametric Conditional Local Independence Testingcited by 7
  11. 2024Learning Granger Causality from Instance-wise Self-attentive Hawkes Processescited by 7
  12. 2023Modeling Events and Interactions through Temporal Processes -- A Surveycited by 5
26 more
  1. 2023Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message Lengthcited by 3
  2. 2023Self-supervised Adaptive Pre-training of Multilingual Speech Models for Language and Dialect Identificationcited by 2
  3. 2025Advances in Temporal Point Processes: Bayesian, Neural, and LLM Approachescited by 2
  4. 2026Your Autoregressive Model Already Reveals the Causal Graphcited by 2
  5. 2026Causal Representation Meets Stochastic Modeling under Generic Geometrycited by 2
  6. 2023A neural network based model for multi-dimensional nonlinear Hawkes processescited by 1
  7. 2025Likelihood-Free Estimation for Spatiotemporal Hawkes processes with missing data and application to predictive policingcited by 1
  8. 2021Signal Transformer: Complex-valued Attention and Meta-Learning for Signal Recognitioncited by 0
  9. 2021Local Independence Testing for Point Processescited by 0
  10. 2023Hawkes Processes with Delayed Granger Causalitycited by 0
  11. 2023Detecting Structural Shifts in Multivariate Hawkes Processes with Fr'echet Statisticscited by 0
  12. 2023Enhancing Asynchronous Time Series Forecasting with Contrastive Relational Inferencecited by 0
  13. 2023Enhancing Multilingual Speech Recognition through Language Prompt Tuning and Frame-Level Language Adaptercited by 0
  14. 2023GMTR: Graph Matching Transformerscited by 0
  15. 2023DarkShot: Lighting Dark Images with Low-Compute and High-Qualitycited by 0
  16. 2024TRLS: A Time Series Representation Learning Framework via Spectrogram for Medical Signal Processingcited by 0
  17. 2024TEN-GUARD: Tensor Decomposition for Backdoor Attack Detection in Deep Neural Networkscited by 0
  18. 2024T-Pixel2Mesh: Combining Global and Local Transformer for 3D Mesh Generation from a Single Imagecited by 0
  19. 2024Strategic Arms with Side Communication Prevail Over Low-Regret MAB Algorithmscited by 0
  20. 2024Towards General Deepfake Detection with Dynamic Curriculumcited by 0
  21. 2024Attr-Int: A Simple and Effective Entity Alignment Framework for Heterogeneous Knowledge Graphscited by 0
  22. 2025Sparklen: A Statistical Learning Toolkit for High-Dimensional Hawkes Processes in Pythoncited by 0
  23. 2025Spectral clustering for dependent community Hawkes process models of temporal networkscited by 0
  24. 2025Mask6D: Masked Pose Priors For 6D Object Pose Estimationcited by 0
  25. 2025Causal Structure Learning in Hawkes Processes with Complex Latent Confounder Networkscited by 0
  26. 2026On Observation Time for Recovering Latent Hawkes Networkscited by 0