Liang, Yurou; Zadorozhnyi, Oleksandr; Drton, Mathias
Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical Models
253-272
Proceedings of Machine Learning Research
Proceedings of The 12th International Conference on Probabilistic Graphical Models
ML Research Press
2024

Strieder, David; Drton, Mathias
Identifying Total Causal Effects in Linear Models under Partial Homoscedasticity
213-230
Proceedings of Machine Learning Research
Proceedings of The 12th International Conference on Probabilistic Graphical Models
ML Research Press
2024

Strieder, David; Drton, Mathias
Dual Likelihood for Causal Inference under Structure Uncertainty
Preprint
2024

Drton, Mathias; Grosdos, Alexandros; McCormack, Andrew
Rational Maximum Likelihood Estimators of Kronecker Covariance Matrices
Preprint
2024

Drton, Mathias; Henckel, Leonard; Hollering, Benjamin; Misra, Pratik
Faithlessness in Gaussian graphical models
Preprint
2024

Tramontano, Daniele; Drton, Mathias; Etesami, Jalal
Parameter identification in linear non-Gaussian causal models under general confounding
Preprint
2024

Tramontano, Daniele; Kivva, Yaroslav; Salehkaleybar, Saber; Drton, Mathias; Kiyavash, Negar
Causal Effect Identification in LiNGAM Models with Latent Confounders
Preprint
2024

Shi, Hongjian; Drton, Mathias
On universal inference in Gaussian mixture models
Preprint
2024

Boege, Tobias; Drton, Mathias; Hollering, Benjamin; Lumpp, Sarah; Misra, Pratik; Schkoda, Daniela
Conditional Independence in Stationary Diffusions
Preprint
2024

Schkoda, Daniela; Robeva, Elina; Drton, Mathias
Causal Discovery of Linear Non-Gaussian Causal Models with Unobserved Confounding
Preprint
2024