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#p-drton

Efficient Learning of Stationary Diffusions With Stein-Type Discrepancies

AISTATS 2026

#p-drton

On the Distance Between Mean and Geometric Median in High Dimensions

Statistics and Probability Letters Early Access.110679. Feb. 2026

#p-drton

Matching Criterion for Identifiability in Sparse Factor Analysis

Preprint (Jan. 2026)

#p-drton

On Weak Convergence of Gaussian Conditional Distributions

Statistics and Probability Letters 226.110497. Nov. 2025

#p-drton

Confidence Sets for Causal Orderings

Journal of the American Statistical Association. Oct. 2025

#p-drton

Identifying Total Causal Effects in Linear Models Under Partial Homoscedasticity

International Journal of Approximate Reasoning 183.109455. Aug. 2025

#p-drton

Causal Discovery for Linear Non-Gaussian Models With Disjoint Cycles

UAI 2025

#p-drton

Causal Effect Identification in LvLiNGAM From Higher-Order Cumulants

ICML 2025

#p-drton

Single-Cell Differential Expression Analysis Between Conditions Within Nested Settings

Briefings in Bioinformatics 26.4. Jul. 2025

#p-drton

Trek-Based Parameter Identification for Linear Causal Models With Arbitrarily Structured Latent Variables

Preprint (Jul. 2025)

#p-drton

Conditional Independence in Stationary Distributions of Diffusions

Stochastic Processes and Their Applications 184.104604. Jun. 2025

#p-drton

Nonlinear Causal Discovery for Grouped Data

Preprint (Jun. 2025)

#p-drton

Structure Uncertainty in Causal Inference

Dissertation TU München. May. 2025

#p-drton

On Universal Inference in Gaussian Mixture Models

Preprint (Mar. 2025)

#p-drton

Algebraic Sparse Factor Analysis

SIAM Journal on Applied Algebra and Geometry 9. Feb. 2025

#p-drton

Existence of Direct Density Ratio Estimators

Preprint (Feb. 2025)

#p-drton

Robust Score Matching

Preprint (Jan. 2025)

#p-drton

Identifiability and Statistical Inference in Latent Variable Modeling

Dissertation TU München. Sep. 2024

#p-drton

Kernel-Based Differentiable Learning of Non-Parametric Directed Acyclic Graphical Models

PGM 2024

#p-drton

Identifying Total Causal Effects in Linear Models Under Partial Homoscedasticity

PGM 2024

#p-drton

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

Preprint (Aug. 2024)

#p-drton

Causal Effect Identification in LiNGAM Models With Latent Confounders

ICML 2024

#p-drton

High-Dimensional Undirected Graphical Models for Arbitrary Mixed Data

Electronic Journal of Statistics 18.1. Jun. 2024

#p-drton

On the Lasso for Graphical Continuous Lyapunov Models

CLeaR 2024

#p-drton

CausalAssembly: Generating Realistic Production Data for Benchmarking Causal Discovery

CLeaR 2024

#p-drton

Dual Likelihood for Causal Inference Under Structure Uncertainty

CLeaR 2024

#p-drton

Testing Many Constraints in Possibly Irregular Models Using Incomplete U-Statistics

Journal of the Royal Statistical Society. Series B (Statistical Methodology) 86.4. Mar. 2024

#p-drton

Unpaired Multi-Domain Causal Representation Learning

NeurIPS 2023

#p-drton

Confidence in Causal Inference Under Structure Uncertainty in Linear Causal Models With Equal Variances

Journal of Causal Inference 11.1. Dec. 2023

#p-drton

Rank-Based Causal Discovery for Post-Nonlinear Models

AISTATS 2023

#p-drton

Half-Trek Criterion for Identifiability of Latent Variable Models

Annals of Statistics 50.6. Dec. 2022

#p-drton

On the Choice of the Splitting Ratio for the Split Likelihood Ratio Test

Electronic Journal of Statistics 16.2. Mar. 2022

#p-drton