mlsanityData to 14 Oct 2026

CausalDynamics: A large-scale benchmark for structural discovery of dynamical causal models

arXiv 2505.16620 ↗First posted 22 May 2025cs.LGcited by 8

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Abstract (arXiv)

Causal discovery for dynamical systems poses a major challenge in fields where active interventions are infeasible. Most methods used to investigate these systems and their associated benchmarks are tailored to deterministic, low-dimensional and weakly nonlinear time-series data. To address these limitations, we present CausalDynamics, a large-scale benchmark and extensible data generation framework to advance the structural discovery of dynamical causal models. Our benchmark consists of true causal graphs derived from thousands of both linearly and nonlinearly coupled ordinary and stochastic differential equations as well as two idealized climate models. We perform a comprehensive evaluation of state-of-the-art causal discovery algorithms for graph reconstruction on systems with noisy, confounded, and lagged dynamics. CausalDynamics consists of a plug-and-play, build-your-own coupling workflow that enables the construction of a hierarchy of physical systems. We anticipate that our framework will facilitate the development of robust causal discovery algorithms that are broadly applicable across domains while addressing their unique challenges. We provide a user-friendly implementation and documentation on https://kausable.github.io/CausalDynamics.

Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 40 of its 110 references that are in the map. First posted on arXiv 22 May 2025.

Builds on

40 of 110 references.

References · 40

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28 more
  1. 2022Greedy Relaxations of the Sparsest Permutation Algorithmcited by 64
  2. 2019Economy Statistical Recurrent Units For Inferring Nonlinear Granger Causalitycited by 55
  3. 2024ChaosBench: A Multi-Channel, Physics-Based Benchmark for Subseasonal-to-Seasonal Climate Predictioncited by 43
  4. 2021Neural graphical modelling in continuous-time: consistency guarantees and algorithmscited by 42
  5. 2014From Ordinary Differential Equations to Structural Causal Models: the deterministic casecited by 41
  6. 2023CUTS+: High-dimensional Causal Discovery from Irregular Time-seriescited by 41
  7. 2023CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discoverycited by 36
  8. 2020Causal models for dynamical systemscited by 34
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  11. 2023A Scale-Invariant Sorting Criterion to Find a Causal Order in Additive Noise Modelscited by 28
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  15. 2021Data Generating Process to Evaluate Causal Discovery Techniques for Time Series Datacited by 22
  16. 2023textttcausalAssembly: Generating Realistic Production Data for Benchmarking Causal Discoverycited by 18
  17. 2024The Landscape of Causal Discovery Data: Grounding Causal Discovery in Real-World Applicationscited by 18
  18. 2023Enhancing Causal Discovery from Robot Sensor Data in Dynamic Scenarioscited by 17
  19. 2024Standardizing Structural Causal Modelscited by 17
  20. 2013Structural Intervention Distance (SID) for Evaluating Causal Graphscited by 14
  21. 2024Dynamic Structural Causal Modelscited by 14
  22. 2025Unitless Unrestricted Markov-Consistent SCM Generation: Better Benchmark Datasets for Causal Discoverycited by 8
  23. 2023The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation datacited by 7
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  25. 2021Using Non-Linear Causal Models to Study Aerosol-Cloud Interactions in the Southeast Pacificcited by 6
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 8.

8 papers.

  1. 2026TCD-Arena: Assessing Robustness of Time Series Causal Discovery Methods Against Assumption Violationscited by 0
  2. 2026In-context learning to predict critical transitions in dynamical systemscited by 0
  3. 2026Trio: Learning Time-Series Forecasting with Temporal-Spatial-Sample Attention and Structural Causal Priorscited by 0
  4. 2026AutoCause: A Python framework that automates expert decisions in environmental time-series causal discoverycited by 0
  5. 2026Koopman early warning signals for bifurcation and rate-induced tippingcited by 0
  6. 2026CausalArena: Benchmarking Causal Discovery in the Foundation Model Eracited by 0
  7. 2026Learning Hierarchical Causal Representations of the Effects of Forcings on Temperature in Climate Modelscited by 0
  8. 2026Identifiability Guarantees for Drivers and Dynamics of Delayed Physical Systemscited by 0