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08/18/2022
Pathway to Future Symbiotic Creativity
This report presents a comprehensive view of our vision on the developme...
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06/17/2022
Reframed GES with a Neural Conditional Dependence Measure
In a nonparametric setting, the causal structure is often identifiable o...
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06/08/2022
What-Is and How-To for Fairness in Machine Learning: A Survey, Reflection, and Perspective
Algorithmic fairness has attracted increasing attention in the machine l...
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04/11/2022
Markov categories, causal theories, and the do-calculus
We give a category-theoretic treatment of causal models that formalizes ...
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01/14/2022
Reliable Causal Discovery with Improved Exact Search and Weaker Assumptions
Many of the causal discovery methods rely on the faithfulness assumption...
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01/11/2022
Ancestral instrument method for causal inference without a causal graph
Unobserved confounding is the main obstacle to causal effect estimation ...
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06/10/2020
Low Rank Directed Acyclic Graphs and Causal Structure Learning
Despite several important advances in recent years, learning causal stru...
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06/06/2019
ASP-based Discovery of Semi-Markovian Causal Models under Weaker Assumptions
In recent years the possibility of relaxing the so-called Faithfulness a...
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03/05/2019
Causal Discovery and Hidden Driving Force Estimation from Nonstationary/Heterogeneous Data
It is commonplace to encounter nonstationary or heterogeneous data. Such...
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12/15/2018
Causal Identification under Markov Equivalence
Assessing the magnitude of cause-and-effect relations is one of the cent...
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02/20/2018
How to Tackle an Extremely Hard Learning Problem: Learning Causal Structures from Non-Experimental Data without the Faithfulness Assumption or the Like
Most methods for learning causal structures from non-experimental data r...
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09/27/2015
Discovery and Visualization of Nonstationary Causal Models
It is commonplace to encounter nonstationary data, of which the underlyi...
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04/22/2015
Distinguishing Cause from Effect Based on Exogeneity
Recent developments in structural equation modeling have produced severa...
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10/19/2012
Strong Faithfulness and Uniform Consistency in Causal Inference
A fundamental question in causal inference is whether it is possible to ...
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07/04/2012
A Transformational Characterization of Markov Equivalence for Directed Acyclic Graphs with Latent Variables
Different directed acyclic graphs (DAGs) may be Markov equivalent in the...
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07/04/2012
Towards Characterizing Markov Equivalence Classes for Directed Acyclic Graphs with Latent Variables
It is well known that there may be many causal explanations that are con...
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06/20/2012