Graphical Models for Complex Multivariate Data

Project Information

GRAPHMODE

Grant agreement ID: 883818

DOI

10.3030/883818

EC signature date 27 April 2020

Start date 1 October 2020

End date 30 September 2026

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 971 296,00

EU contribution

€ 1 971 296,00

Coordinated by

TECHNISCHE UNIVERSITAET MUENCHEN
Germany

CORDIS provides links to public deliverables and publications of HORIZON projects.

Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Publications

Other (15)

Faithlessness in Gaussian graphical models

Author(s): Mathias Drton, Leonard Henckel, Benjamin Hollering, Pratik Misra
Published in: 2024
Publisher: ArXiv
DOI: 10.48550/arxiv.2404.05306

causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery

Author(s): Konstantin Göbler, Tobias Windisch, Tim Pychynski, Steffen Sonntag, Martin Roth, Mathias Drton
Published in: 2023
Publisher: arXiv
DOI: 10.48550/arxiv.2306.10816

Unpaired Multi-Domain Causal Representation Learning

Author(s): Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler
Published in: Advances in Neural Information Processing Systems 36 (NeurIPS 2023), Issue to appear, 2023
Publisher: arXiv
DOI: 10.48550/arxiv.2302.00993

Confidence Sets for Causal Orderings

Author(s): Y. Samuel Wang, Mladen Kolar, Mathias Drton
Published in: 2023
Publisher: arXiv
DOI: 10.48550/arxiv.2305.14506

Existence of Direct Density Ratio Estimators

Author(s): Erika Banzato, Mathias Drton, Kian Saraf-Poor, Hongjian Shi
Published in: 2025
Publisher: ArXiv

Matching Criterion for Identifiability in Sparse Factor Analysis

Author(s): Nils Sturma, Miriam Kranzlmueller, Irem Portakal, Mathias Drton
Published in: 2025
Publisher: ArXiv

On the Lasso for Graphical Continuous Lyapunov Models

Author(s): Philipp Dettling, Mathias Drton, Mladen Kolar
Published in: 2022
Publisher: arXiv
DOI: 10.48550/arxiv.2208.13572

On universal inference in Gaussian mixture models

Author(s): Hongjian Shi, Mathias Drton
Published in: 2024
Publisher: ArXiv
DOI: 10.48550/arxiv.2407.19361

Identifiability of Homoscedastic Linear Structural Equation Models using Algebraic Matroids

Author(s): Mathias Drton, Benjamin Hollering, Jun Wu
Published in: 2023
Publisher: arXiv
DOI: 10.48550/arxiv.2308.01821

Goodness-of-Fit Tests for Linear Non-Gaussian Structural Equation Models

Author(s): Daniela Schkoda, Mathias Drton
Published in: 2023
Publisher: arXiv
DOI: 10.48550/arxiv.2311.04585

Testing Many and Possibly Singular Polynomial Constraints

Author(s): Nils Sturma, Mathias Drton, Dennis Leung
Published in: 2022
Publisher: arXiv
DOI: 10.48550/arxiv.2208.11756

Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding

Author(s): Daniela Schkoda, Elina Robeva, Mathias Drton
Published in: 2024
Publisher: ArXiv
DOI: 10.48550/arxiv.2408.04907

Colored Gaussian DAG models

Author(s): Tobias Boege, Kaie Kubjas, Pratik Misra, Liam Solus
Published in: 2024
Publisher: ArXiv
DOI: 10.48550/arxiv.2404.04024

Identifiability in Continuous Lyapunov Models

Author(s): Philipp Dettling, Roser Homs, Carlos Améndola, Mathias Drton, Niels Richard Hansen
Published in: 2022
Publisher: arXiv
DOI: 10.48550/arxiv.2209.03835

Parametric and nonparametric symmetries in graphical models for extremes

Author(s): Röttger, Frank; Coons, Jane Ivy; Grosdos, Alexandros
Published in: Issue 1, 2023
Publisher: ArXiv
DOI: 10.48550/arxiv.2306.00703

Conference proceedings (12)

Directed Graphical Models and Causal Discovery for Zero-Inflated Data

Author(s): Shiqing Yu, Mathias Drton, Ali Shojaie
Published in: Proceedings of the Second Conference on Causal Learning and Reasoning, Issue 213, 2023, Page(s) 27-67
Publisher: PMLR

Causal Effect Identification in LiNGAM Models with Latent Confounders

Author(s): Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar, Mathias Drton, Negar Kiyavash
Published in: Proceedings of the 41st International Conference on Machine Learning, Issue 235, 2024
Publisher: Proceedings of Machine Learning Research (PMLR)

Interaction Models and Generalized Score Matching for Compositional Data

Author(s): Shiqing Yu, Mathias Drton, and Ali Shojaie
Published in: Proceedings of the Second Learning on Graphs Conference, Issue 231, 2024
Publisher: Proceedings of Machine Learning Research (PMLR)

Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity

Author(s): David Strieder, Mathias Drton
Published in: Proceedings of the 12th International Conference on Probabilistic Graphical Models, Issue 246, 2024
Publisher: Proceedings of Machine Learning Research (PMLR)

Rank-Based Causal Discovery for Post-Nonlinear Models

Author(s): Grigor Keropyan, David Strieder, Mathias Drton
Published in: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, 2023, Page(s) 7849-7870
Publisher: PMLR Proceedings of Machine Learning Research

Definite Non-Ancestral Relations and Structure Learning

Author(s): Wenyu Chen, Mathias Drton, Ali Shojaie
Published in: 8th Causal Inference Workshop at UAI, 2021, Page(s) "Paper #2"
Publisher: causalUAI2021

Robust Score Matching

Author(s): Richard Schwank, Andrew McCormack, Mathias Drton
Published in: Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Publisher: Proceedings of Machine Learning Research (PMLR)

Learning Linear Non-Gaussian Polytree Models

Author(s): Daniele Tramontano, Anthea Monod, Mathias Drton
Published in: Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, Issue Proceedings of Machine Learning Research 180, 2022, Page(s) 1960-1969
Publisher: PMLR
DOI: 10.48550/arxiv.2208.06701

Confidence in Causal Discovery with Linear Causal Models

Author(s): David Strieder, Tobias Freidling, Stefan Haffner, Mathias Drton
Published in: Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, Issue PMLR 161, 2021, Page(s) 1217-1226
Publisher: Proceedings of Machine Learning Research

Dual Likelihood for Causal Inference under Structure Uncertainty

Author(s): David Strieder, Mathias Drton
Published in: Proceedings of the 3rd Conference on Causal Learning and Reasoning, Issue 236, 2024
Publisher: Proceedings of Machine Learning Research (PMLR)

Center-Outward Sign- and Rank-Based Quadrant, Spearman, and Kendall Tests for Multivariate Independence

Author(s): Hongjian Shi, Mathias Drton, Marc Hallin, Fang Han
Published in: OT-SDM 2022: The 1st International Workshop on Optimal Transport and Structured Data Modeling, 2022
Publisher: AAAI 2022

Graphical Representations for Algebraic Constraints of Linear Structural Equations Models

Author(s): Thijs van Ommen, Mathias Drton
Published in: Proceedings of The 11th International Conference on Probabilistic Graphical Models, Issue 186, 2022, Page(s) 409-420
Publisher: Proceedings of Machine Learning Research (PMLR)
DOI: 10.48550/arxiv.2208.00926

Peer reviewed articles (18)

Rational maximum likelihood estimators of Kronecker covariance matrices

Author(s): Mathias Drton, Alexandros Grosdos, Andrew McCormack
Published in: Algebraic Statistics, Issue 15, 2024, Page(s) 145-164, ISSN 2693-3004
Publisher: Mathematical Sciences Publishers
DOI: 10.2140/astat.2024.15.145

Partial Homoscedasticity in Causal Discovery with Linear Models

Author(s): Jun Wu, Mathias Drton
Published in: IEEE Journal on Selected Areas in Information Theory, 2023, ISSN 2641-8770
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/jsait.2023.3328476

Learning Linear Gaussian Polytree Models With Interventions

Author(s): Daniele Tramontano, Leonard Waldmann, Mathias Drton, Eliana Duarte
Published in: IEEE Journal on Selected Areas in Information Theory, 2023, ISSN 2641-8770
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
DOI: 10.1109/jsait.2023.3328429

Half-Trek Criterion for Identifiability of Latent Variable Models

Author(s): Rina Foygel Barber, Mathias Drton, Nils Sturma, Luca Weihs
Published in: The Annals of Statistics, Issue 50, 2022, Page(s) 3174-3196, ISSN 0090-5364
Publisher: Institute of Mathematical Statistics
DOI: 10.1214/22-aos2221

On the choice of the splitting ratio for the split likelihood ratio test

Author(s): David Strieder, Mathias Drton
Published in: Electronic Journal of Statistics, Issue 16, 2022, Page(s) 6631-6650, ISSN 1935-7524
Publisher: Institute of Mathematical Statistics
DOI: 10.1214/22-ejs2099

Causal Structural Learning via Local Graphs

Author(s): Wenyu Chen, Mathias Drton, Ali Shojaie
Published in: SIAM Journal on Mathematics of Data Science, Issue 5(2), 2023, Page(s) 280-305, ISSN 2577-0187
Publisher: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m1362796

"Discussion of ""A note on universal inference"" by Timmy Tse and Anthony Davison"

Author(s): Mathias Drton, Hongjian Shi, David Strieder
Published in: Stat, Issue 12(1), 2023, Page(s) e574, ISSN 2049-1573
Publisher: Wiley
DOI: 10.1002/sta4.572

On Azadkia–Chatterjee’s conditional dependence coefficient

Author(s): Hongjian Shi, Mathias Drton, Fang Han
Published in: Bernoulli, Issue 30, 2024, ISSN 1350-7265
Publisher: Chapman & Hall
DOI: 10.3150/22-bej1529

On the power of Chatterjee’s rank correlation

Author(s): Hongjian Shi, Mathias Drton, Fang Han
Published in: Biometrika, 2021, ISSN 0006-3444
Publisher: Oxford University Press
DOI: 10.1093/biomet/asab028

Algebraic Sparse Factor Analysis

Author(s): Mathias Drton, Alexandros Grosdos, Irem Portakal, Nils Sturma
Published in: SIAM Journal on Applied Algebra and Geometry, Issue 9, 2025, Page(s) 279-309, ISSN 2470-6566
Publisher: Society for Industrial & Applied Mathematics (SIAM)
DOI: 10.1137/23m1626517

Homaloidal polynomials and Gaussian models of maximum likelihood degree 1

Author(s): Shelby Cox, Pratik Misra, Pardis Semnani
Published in: Algebraic Statistics, Issue 15, 2024, Page(s) 167-198, ISSN 2693-3004
Publisher: Mathematical Sciences Publishers
DOI: 10.2140/astat.2024.15.167

Third-Order Moment Varieties of Linear Non-Gaussian Graphical Models

Author(s): Carlos Améndola, Mathias Drton, Alexandros Grosdos, Roser Homs, Elina Robeva
Published in: Information and Inference. A Journal of the IMA, Issue 12(3), 2023, Page(s) iaad007, ISSN 2049-8764
Publisher: Oxford University Press
DOI: 10.1093/imaiai/iaad007

Confidence in Causal Inference under Structure Uncertainty in Linear Causal Models with Equal Variances

Author(s): David Strieder, Mathias Drton
Published in: Journal of Causal Inference, Issue to appear, 2023, ISSN 2193-3685
Publisher: De Gruyter

On universally consistent and fully distribution-free rank tests of vector independence

Author(s): Hongjian Shi, Marc Hallin, Mathias Drton, Fang Han
Published in: The Annals of Statistics, Issue 50, 2022, Page(s) 1933-1959, ISSN 0090-5364
Publisher: Institute of Mathematical Statistics
DOI: 10.1214/21-aos2151

High-dimensional undirected graphical models for arbitrary mixed data

Author(s): Konstantin Göbler, Mathias Drton, Sach Mukherjee, Anne Miloschewski
Published in: Electronic Journal of Statistics, Issue 18, 2024, ISSN 1935-7524
Publisher: Institute of Mathematical Statistics
DOI: 10.1214/24-ejs2254

Distribution-free tests of multivariate independence based on center-outward quadrant, Spearman, Kendall, and van der Waerden statistics

Author(s): Hongjian Shi, Mathias Drton, Marc Hallin, Fang Han
Published in: Bernoulli, Issue 31, 2025, Page(s) 106-129, ISSN 1350-7265
Publisher: Chapman & Hall
DOI: 10.3150/24-bej1721

Conditional independence in stationary distributions of diffusions

Author(s): Tobias Boege, Mathias Drton, Benjamin Hollering, Sarah Lumpp, Pratik Misra, Daniela Schkoda
Published in: Stochastic Processes and their Applications, Issue 184, 2025, Page(s) 104604, ISSN 0304-4149
Publisher: Elsevier BV
DOI: 10.1016/j.spa.2025.104604

Causal Discovery with Unobserved Confounding and non-Gaussian Data

Author(s): Y. Samuel Wang, Mathias Drton
Published in: Journal of Machine Learning Research, Issue 271, 2023, Page(s) 1−61, ISSN 1533-7928
Publisher: JMLR, Inc.
DOI: 10.48550/arxiv.2007.11131

Thesis and dissertations (3)

Identifiability and Statistical Inference in Latent Variable Modeling

Author(s): Sturma, Nils B.
Published in: 2024
Publisher: online

Homoscedasticity and Feedback Loops in Graphical Models

Author(s): Wu, Jun
Published in: Issue 5, 2023
Publisher: Technical University of Munich

Graphical Continuous Lyapunov Models

Author(s): Dettling, Philipp Maximilian
Published in: 2024
Publisher: online