activity
20152022
most citedCausal Explanations and XAI

13 citations · 18 across the 4 of their papers we have counts for

collaborators

7 papers

cs.AI202213 cited

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.…

cs.AI2021

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…

cs.AI2020

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…

cs.AI2020

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…

cs.AI20193 cited

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…

cs.AI2018

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…