106 citations · 200 across the 12 of their papers we have counts for
13 papers
On Probabilistic and Causal Reasoning with Summation Operators
Duligur Ibeling, Thomas F. Icard, Milan Mossé
Ibeling et al. (2023). axiomatize increasingly expressive languages of causation and probability, and Mosse et al. (2024) show that reasoning (specifically the satisfiability probl…
Probing the Quantitative-Qualitative Divide in Probabilistic Reasoning
Duligur Ibeling, Thomas Icard, Krzysztof Mierzewski +1
This paper explores the space of (propositional) probabilistic logical languages, ranging from a purely `qualitative' comparative language to a highly `quantitative' language invol…
Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
Duligur Ibeling, Thomas Icard
The aim of this paper is to make clear and precise the relationship between the Rubin causal model (RCM) and structural causal model (SCM) frameworks for causal inference. Adopting…
Causal Abstraction: A Theoretical Foundation for Mechanistic Interpretability
Atticus Geiger, Duligur Ibeling, Amir Zur +8
Causal abstraction provides a theoretical foundation for mechanistic interpretability, the field concerned with providing intelligible algorithms that are faithful simplifications…
Is Causal Reasoning Harder than Probabilistic Reasoning?
Milan Mossé, Duligur Ibeling, Thomas Icard
Many tasks in statistical and causal inference can be construed as problems of \emph{entailment} in a suitable formal language. We ask whether those problems are more difficult, fr…
A Topological Perspective on Causal Inference
Duligur Ibeling, Thomas Icard
This paper presents a topological learning-theoretic perspective on causal inference by introducing a series of topologies defined on general spaces of structural causal models (SC…