Graphical Models for Complex Multivariate Data

Información del proyecto

GRAPHMODE

Identificador del acuerdo de subvención: 883818

DOI

10.3030/883818

Fecha de la firma de la CE 27 Abril 2020

Fecha de inicio 1 Octubre 2020

Fecha de finalización 30 Septiembre 2026

Financiado con arreglo a

• EXCELLENT SCIENCE - European Research Council (ERC)

Coste total

€ 1 971 296,00

Aportación de la UE

€ 1 971 296,00

Coordinado por

TECHNISCHE UNIVERSITAET MUENCHEN
Germany

CORDIS proporciona enlaces a los documentos públicos y las publicaciones de los proyectos de los programas marco HORIZONTE.

Los enlaces a los documentos y las publicaciones de los proyectos del Séptimo Programa Marco, así como los enlaces a algunos tipos de resultados específicos, como conjuntos de datos y «software», se obtienen dinámicamente de OpenAIRE .

Publicaciones

Other (15)

Faithlessness in Gaussian graphical models

Autores: Mathias Drton, Leonard Henckel, Benjamin Hollering, Pratik Misra
Publicado en: 2024
Editor: ArXiv
DOI: 10.48550/arxiv.2404.05306

causalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery

Autores: Konstantin Göbler, Tobias Windisch, Tim Pychynski, Steffen Sonntag, Martin Roth, Mathias Drton
Publicado en: 2023
Editor: arXiv
DOI: 10.48550/arxiv.2306.10816

Unpaired Multi-Domain Causal Representation Learning

Autores: Nils Sturma, Chandler Squires, Mathias Drton, Caroline Uhler
Publicado en: Advances in Neural Information Processing Systems 36 (NeurIPS 2023), Edición to appear, 2023
Editor: arXiv
DOI: 10.48550/arxiv.2302.00993

Confidence Sets for Causal Orderings

Autores: Y. Samuel Wang, Mladen Kolar, Mathias Drton
Publicado en: 2023
Editor: arXiv
DOI: 10.48550/arxiv.2305.14506

Existence of Direct Density Ratio Estimators

Autores: Erika Banzato, Mathias Drton, Kian Saraf-Poor, Hongjian Shi
Publicado en: 2025
Editor: ArXiv

Matching Criterion for Identifiability in Sparse Factor Analysis

Autores: Nils Sturma, Miriam Kranzlmueller, Irem Portakal, Mathias Drton
Publicado en: 2025
Editor: ArXiv

On the Lasso for Graphical Continuous Lyapunov Models

Autores: Philipp Dettling, Mathias Drton, Mladen Kolar
Publicado en: 2022
Editor: arXiv
DOI: 10.48550/arxiv.2208.13572

On universal inference in Gaussian mixture models

Autores: Hongjian Shi, Mathias Drton
Publicado en: 2024
Editor: ArXiv
DOI: 10.48550/arxiv.2407.19361

Identifiability of Homoscedastic Linear Structural Equation Models using Algebraic Matroids

Autores: Mathias Drton, Benjamin Hollering, Jun Wu
Publicado en: 2023
Editor: arXiv
DOI: 10.48550/arxiv.2308.01821

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

Autores: Daniela Schkoda, Mathias Drton
Publicado en: 2023
Editor: arXiv
DOI: 10.48550/arxiv.2311.04585

Testing Many and Possibly Singular Polynomial Constraints

Autores: Nils Sturma, Mathias Drton, Dennis Leung
Publicado en: 2022
Editor: arXiv
DOI: 10.48550/arxiv.2208.11756

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

Autores: Daniela Schkoda, Elina Robeva, Mathias Drton
Publicado en: 2024
Editor: ArXiv
DOI: 10.48550/arxiv.2408.04907

Colored Gaussian DAG models

Autores: Tobias Boege, Kaie Kubjas, Pratik Misra, Liam Solus
Publicado en: 2024
Editor: ArXiv
DOI: 10.48550/arxiv.2404.04024

Identifiability in Continuous Lyapunov Models

Autores: Philipp Dettling, Roser Homs, Carlos Améndola, Mathias Drton, Niels Richard Hansen
Publicado en: 2022
Editor: arXiv
DOI: 10.48550/arxiv.2209.03835

Parametric and nonparametric symmetries in graphical models for extremes

Autores: Röttger, Frank; Coons, Jane Ivy; Grosdos, Alexandros
Publicado en: Edición 1, 2023
Editor: ArXiv
DOI: 10.48550/arxiv.2306.00703

Conference proceedings (12)

Directed Graphical Models and Causal Discovery for Zero-Inflated Data

Autores: Shiqing Yu, Mathias Drton, Ali Shojaie
Publicado en: Proceedings of the Second Conference on Causal Learning and Reasoning, Edición 213, 2023, Página(s) 27-67
Editor: PMLR

Causal Effect Identification in LiNGAM Models with Latent Confounders

Autores: Daniele Tramontano, Yaroslav Kivva, Saber Salehkaleybar, Mathias Drton, Negar Kiyavash
Publicado en: Proceedings of the 41st International Conference on Machine Learning, Edición 235, 2024
Editor: Proceedings of Machine Learning Research (PMLR)

Interaction Models and Generalized Score Matching for Compositional Data

Autores: Shiqing Yu, Mathias Drton, and Ali Shojaie
Publicado en: Proceedings of the Second Learning on Graphs Conference, Edición 231, 2024
Editor: Proceedings of Machine Learning Research (PMLR)

Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity

Autores: David Strieder, Mathias Drton
Publicado en: Proceedings of the 12th International Conference on Probabilistic Graphical Models, Edición 246, 2024
Editor: Proceedings of Machine Learning Research (PMLR)

Rank-Based Causal Discovery for Post-Nonlinear Models

Autores: Grigor Keropyan, David Strieder, Mathias Drton
Publicado en: Proceedings of The 26th International Conference on Artificial Intelligence and Statistics, 2023, Página(s) 7849-7870
Editor: PMLR Proceedings of Machine Learning Research

Definite Non-Ancestral Relations and Structure Learning

Autores: Wenyu Chen, Mathias Drton, Ali Shojaie
Publicado en: 8th Causal Inference Workshop at UAI, 2021, Página(s) "Paper #2"
Editor: causalUAI2021

Robust Score Matching

Autores: Richard Schwank, Andrew McCormack, Mathias Drton
Publicado en: Proceedings of the 28th International Conference on Artificial Intelligence and Statistics (AISTATS), 2025
Editor: Proceedings of Machine Learning Research (PMLR)

Learning Linear Non-Gaussian Polytree Models

Autores: Daniele Tramontano, Anthea Monod, Mathias Drton
Publicado en: Proceedings of the Thirty-Eighth Conference on Uncertainty in Artificial Intelligence, Edición Proceedings of Machine Learning Research 180, 2022, Página(s) 1960-1969
Editor: PMLR
DOI: 10.48550/arxiv.2208.06701

Confidence in Causal Discovery with Linear Causal Models

Autores: David Strieder, Tobias Freidling, Stefan Haffner, Mathias Drton
Publicado en: Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, Edición PMLR 161, 2021, Página(s) 1217-1226
Editor: Proceedings of Machine Learning Research

Dual Likelihood for Causal Inference under Structure Uncertainty

Autores: David Strieder, Mathias Drton
Publicado en: Proceedings of the 3rd Conference on Causal Learning and Reasoning, Edición 236, 2024
Editor: Proceedings of Machine Learning Research (PMLR)

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

Autores: Hongjian Shi, Mathias Drton, Marc Hallin, Fang Han
Publicado en: OT-SDM 2022: The 1st International Workshop on Optimal Transport and Structured Data Modeling, 2022
Editor: AAAI 2022

Graphical Representations for Algebraic Constraints of Linear Structural Equations Models

Autores: Thijs van Ommen, Mathias Drton
Publicado en: Proceedings of The 11th International Conference on Probabilistic Graphical Models, Edición 186, 2022, Página(s) 409-420
Editor: Proceedings of Machine Learning Research (PMLR)
DOI: 10.48550/arxiv.2208.00926

Peer reviewed articles (18)

Rational maximum likelihood estimators of Kronecker covariance matrices

Autores: Mathias Drton, Alexandros Grosdos, Andrew McCormack
Publicado en: Algebraic Statistics, Edición 15, 2024, Página(s) 145-164, ISSN 2693-3004
Editor: Mathematical Sciences Publishers
DOI: 10.2140/astat.2024.15.145

Partial Homoscedasticity in Causal Discovery with Linear Models

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

Learning Linear Gaussian Polytree Models With Interventions

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

Half-Trek Criterion for Identifiability of Latent Variable Models

Autores: Rina Foygel Barber, Mathias Drton, Nils Sturma, Luca Weihs
Publicado en: The Annals of Statistics, Edición 50, 2022, Página(s) 3174-3196, ISSN 0090-5364
Editor: Institute of Mathematical Statistics
DOI: 10.1214/22-aos2221

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

Autores: David Strieder, Mathias Drton
Publicado en: Electronic Journal of Statistics, Edición 16, 2022, Página(s) 6631-6650, ISSN 1935-7524
Editor: Institute of Mathematical Statistics
DOI: 10.1214/22-ejs2099

Causal Structural Learning via Local Graphs

Autores: Wenyu Chen, Mathias Drton, Ali Shojaie
Publicado en: SIAM Journal on Mathematics of Data Science, Edición 5(2), 2023, Página(s) 280-305, ISSN 2577-0187
Editor: Society for Industrial and Applied Mathematics
DOI: 10.1137/20m1362796

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

Autores: Mathias Drton, Hongjian Shi, David Strieder
Publicado en: Stat, Edición 12(1), 2023, Página(s) e574, ISSN 2049-1573
Editor: Wiley
DOI: 10.1002/sta4.572

On Azadkia–Chatterjee’s conditional dependence coefficient

Autores: Hongjian Shi, Mathias Drton, Fang Han
Publicado en: Bernoulli, Edición 30, 2024, ISSN 1350-7265
Editor: Chapman & Hall
DOI: 10.3150/22-bej1529

On the power of Chatterjee’s rank correlation

Autores: Hongjian Shi, Mathias Drton, Fang Han
Publicado en: Biometrika, 2021, ISSN 0006-3444
Editor: Oxford University Press
DOI: 10.1093/biomet/asab028

Algebraic Sparse Factor Analysis

Autores: Mathias Drton, Alexandros Grosdos, Irem Portakal, Nils Sturma
Publicado en: SIAM Journal on Applied Algebra and Geometry, Edición 9, 2025, Página(s) 279-309, ISSN 2470-6566
Editor: Society for Industrial & Applied Mathematics (SIAM)
DOI: 10.1137/23m1626517

Homaloidal polynomials and Gaussian models of maximum likelihood degree 1

Autores: Shelby Cox, Pratik Misra, Pardis Semnani
Publicado en: Algebraic Statistics, Edición 15, 2024, Página(s) 167-198, ISSN 2693-3004
Editor: Mathematical Sciences Publishers
DOI: 10.2140/astat.2024.15.167

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

Autores: Carlos Améndola, Mathias Drton, Alexandros Grosdos, Roser Homs, Elina Robeva
Publicado en: Information and Inference. A Journal of the IMA, Edición 12(3), 2023, Página(s) iaad007, ISSN 2049-8764
Editor: Oxford University Press
DOI: 10.1093/imaiai/iaad007

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

Autores: David Strieder, Mathias Drton
Publicado en: Journal of Causal Inference, Edición to appear, 2023, ISSN 2193-3685
Editor: De Gruyter

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

Autores: Hongjian Shi, Marc Hallin, Mathias Drton, Fang Han
Publicado en: The Annals of Statistics, Edición 50, 2022, Página(s) 1933-1959, ISSN 0090-5364
Editor: Institute of Mathematical Statistics
DOI: 10.1214/21-aos2151

High-dimensional undirected graphical models for arbitrary mixed data

Autores: Konstantin Göbler, Mathias Drton, Sach Mukherjee, Anne Miloschewski
Publicado en: Electronic Journal of Statistics, Edición 18, 2024, ISSN 1935-7524
Editor: 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

Autores: Hongjian Shi, Mathias Drton, Marc Hallin, Fang Han
Publicado en: Bernoulli, Edición 31, 2025, Página(s) 106-129, ISSN 1350-7265
Editor: Chapman & Hall
DOI: 10.3150/24-bej1721

Conditional independence in stationary distributions of diffusions

Autores: Tobias Boege, Mathias Drton, Benjamin Hollering, Sarah Lumpp, Pratik Misra, Daniela Schkoda
Publicado en: Stochastic Processes and their Applications, Edición 184, 2025, Página(s) 104604, ISSN 0304-4149
Editor: Elsevier BV
DOI: 10.1016/j.spa.2025.104604

Causal Discovery with Unobserved Confounding and non-Gaussian Data

Autores: Y. Samuel Wang, Mathias Drton
Publicado en: Journal of Machine Learning Research, Edición 271, 2023, Página(s) 1−61, ISSN 1533-7928
Editor: JMLR, Inc.
DOI: 10.48550/arxiv.2007.11131

Thesis and dissertations (3)

Identifiability and Statistical Inference in Latent Variable Modeling

Autores: Sturma, Nils B.
Publicado en: 2024
Editor: online

Homoscedasticity and Feedback Loops in Graphical Models

Autores: Wu, Jun
Publicado en: Edición 5, 2023
Editor: Technical University of Munich

Graphical Continuous Lyapunov Models

Autores: Dettling, Philipp Maximilian
Publicado en: 2024
Editor: online