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09/01/2023
Establishing Markov Equivalence in Cyclic Directed Graphs
We present a new, efficient procedure to establish Markov equivalence be...
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03/29/2023
Correcting for Selection Bias and Missing Response in Regression using Privileged Information
When estimating a regression model, we might have data where some labels...
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03/08/2021
Efficient Causal Inference from Combined Observational and Interventional Data through Causal Reductions
Unobserved confounding is one of the main challenges when estimating cau...
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01/28/2021
Causality and independence in perfectly adapted dynamical systems
Perfect adaptation in a dynamical system is the phenomenon that one or m...
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12/08/2020
Robustness of Model Predictions under Extension
Often, mathematical models of the real world are simplified representati...
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10/27/2020
A Weaker Faithfulness Assumption based on Triple Interactions
One of the core assumptions in causal discovery is the faithfulness assu...
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09/16/2020
Causal Discovery for Causal Bandits utilizing Separating Sets
The Causal Bandit is a variant of the classic Bandit problem where an ag...
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08/17/2020
A Bayesian Nonparametric Conditional Two-sample Test with an Application to Local Causal Discovery
The performance of constraint-based causal discovery algorithms is promi...
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07/14/2020
Conditional Independences and Causal Relations implied by Sets of Equations
Real-world systems are often modelled by sets of equations with exogenou...
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05/01/2020
Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles
While feedback loops are known to play important roles in many complex s...
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05/01/2020
Constraint-Based Causal Discovery In The Presence Of Cycles
While feedback loops are known to play important roles in many complex s...
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10/06/2019
Boosting Local Causal Discovery in High-Dimensional Expression Data
We study how well Local Causal Discovery (LCD), a simple and efficient c...
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01/02/2019
Causal Calculus in the Presence of Cycles, Latent Confounders and Selection Bias
We prove the main rules of causal calculus (also called do-calculus) for...
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10/18/2018
An Upper Bound for Random Measurement Error in Causal Discovery
Causal discovery algorithms infer causal relations from data based on se...
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07/10/2018
Algebraic Equivalence of Linear Structural Equation Models
Despite their popularity, many questions about the algebraic constraints...
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07/09/2018
Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders
We address the problem of causal discovery from data, making use of the ...
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05/16/2018
Generalized Strucutral Causal Models
Structural causal models are a popular tool to describe causal relations...
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03/23/2018
From Random Differential Equations to Structural Causal Models: the stochastic case
Random Differential Equations provide a natural extension of Ordinary Di...
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10/24/2017
Markov Properties for Graphical Models with Cycles and Latent Variables
We investigate probabilistic graphical models that allow for both cycles...
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07/20/2017
Causal Transfer Learning
An important goal in both transfer learning and causal inference is to m...
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07/04/2017
Causal Consistency of Structural Equation Models
Complex systems can be modelled at various levels of detail. Ideally, ca...
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11/30/2016
Joint Causal Inference from Observational and Experimental Datasets
We introduce Joint Causal Inference (JCI), a powerful formulation of cau...
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11/18/2016
Structural Causal Models: Cycles, Marginalizations, Exogenous Reparametrizations and Reductions
Structural causal models (SCMs), also known as non-parametric structural...
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06/22/2016
Ancestral Causal Inference
Constraint-based causal discovery from limited data is a notoriously dif...
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12/11/2014
Distinguishing cause from effect using observational data: methods and benchmarks
The discovery of causal relationships from purely observational data is ...
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11/06/2014