3 papers
stat.ML2026
Efficient Symbolic Computations for Identifying Causal Effects
Benjamin Hollering, Pratik Misra, Nils Sturma
Determining identifiability of causal effects from observational data under latent confounding is a central challenge in causal inference. For linear structural causal models, iden…
math.ST2025
Colored Gaussian directed acyclic graphical models
Tobias Boege, Kaie Kubjas, Pratik Misra +1
We study submodels of Gaussian DAG models defined by partial homogeneity constraints imposed on the model error variances and structural coefficients. We represent these models wit…
math.ST2025
Structural Identifiability of Graphical Continuous Lyapunov Models
Carlos Améndola, Tobias Boege, Benjamin Hollering +1
We prove two characterizations of model equivalence of acyclic graphical continuous Lyapunov models (GCLMs) with uncorrelated noise. The first result shows that two graphs are mode…