13 citations · 26 across the 10 of their papers we have counts for
12 papers
Generating Medical Image Counterfactuals using Causal Explanations
David A. Kelly, Tom Yaacov, Nathan Blake +2
Deep learning models have achieved impressive performance in medical image diagnosis, yet their deployment in clinical settings remains constrained by limited explainability. Count…
Causal Models with Constraints
Sander Beckers, Joseph Y. Halpern, Christopher Hitchcock
Causal models have proven extremely useful in offering formal representations of causal relationships between a set of variables. Yet in many situations, there are non-causal relat…
Backtracking Counterfactuals
Julius von Kügelgen, Abdirisak Mohamed, Sander Beckers
Counterfactual reasoning -- envisioning hypothetical scenarios, or possible worlds, where some circumstances are different from what (f)actually occurred (counter-to-fact) -- is ub…
A Causal Analysis of Harm
Sander Beckers, Hana Chockler, Joseph Y. Halpern
As autonomous systems rapidly become ubiquitous, there is a growing need for a legal and regulatory framework to address when and how such a system harms someone. There have been s…
Quantifying Harm
Sander Beckers, Hana Chockler, Joseph Y. Halpern
In earlier work we defined a qualitative notion of harm: either harm is caused, or it is not. For practical applications, we often need to quantify harm; for example, we may want t…
Causal Explanations and XAI
Sander Beckers
Although standard Machine Learning models are optimized for making predictions about observations, more and more they are used for making predictions about the results of actions.…
Causal Sufficiency and Actual Causation
Sander Beckers
Pearl opened the door to formally defining actual causation using causal models. His approach rests on two strategies: first, capturing the widespread intuition that X=x causes Y=y…
The Counterfactual NESS Definition of Causation
Sander Beckers
In previous work with Joost Vennekens I proposed a definition of actual causation that is based on certain plausible principles, thereby allowing the debate on causation to shift a…
Equivalent Causal Models
Sander Beckers
The aim of this paper is to offer the first systematic exploration and definition of equivalent causal models in the context where both models are not made up of the same variables…
Approximate Causal Abstraction
Sander Beckers, Frederick Eberhardt, Joseph Y. Halpern
Scientific models describe natural phenomena at different levels of abstraction. Abstract descriptions can provide the basis for interventions on the system and explanation of obse…
Abstracting Causal Models
Sander Beckers, Joseph Y. Halpern
We consider a sequence of successively more restrictive definitions of abstraction for causal models, starting with a notion introduced by Rubenstein et al. (2017) called exact tra…
Combining Probabilistic, Causal, and Normative Reasoning in CP-logic
Sander Beckers, Joost Vennekens
In recent years the search for a proper formal definition of actual causation -- i.e., the relation of cause-effect as it is instantiated in specific observations, rather than gene…