7 papers
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…
Algebraic Statistics in OSCAR
Tobias Boege, Antony Della Vecchia, Marina Garrote-López +1
We introduce the AlgebraicStatistics section of the OSCAR computer algebra system. We give an overview of its extensible design and highlight its features including serialization o…
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…
Polyhedral Aspects of Maxoids
Tobias Boege, Kamillo Ferry, Benjamin Hollering +1
The conditional independence (CI) relation of a distribution in a max-linear Bayesian network depends on its weight matrix through the -separation criterion. These CI~model…
Conditional Independence in Stationary Diffusions
Tobias Boege, Mathias Drton, Benjamin Hollering +3
Stationary distributions of multivariate diffusion processes have recently been proposed as probabilistic models of causal systems in statistics and machine learning. Motivated by…
Faithlessness in Gaussian graphical models
Mathias Drton, Leonard Henckel, Benjamin Hollering +1
The implication problem for conditional independence (CI) asks whether the fact that a probability distribution obeys a given finite set of CI relations implies that a further CI s…
Identifiability of Homoscedastic Linear Structural Equation Models using Algebraic Matroids
Mathias Drton, Benjamin Hollering, Jun Wu
We consider structural equation models (SEMs), in which every variable is a function of a subset of the other variables and a stochastic error. Each such SEM is naturally associate…