5 papers · 1 filter
P2C: Path to Counterfactuals
Sopam Dasgupta, Sadaf MD Halim, JoaquÃn Arias +2
Machine-learning models are increasingly driving decisions in high-stakes settings, such as finance, law, and hiring, thus, highlighting the need for transparency. However, the key…
MC3G: Model Agnostic Causally Constrained Counterfactual Generation
Sopam Dasgupta, Sadaf MD Halim, JoaquÃn Arias +2
Machine learning models increasingly influence decisions in high-stakes settings such as finance, law and hiring, driving the need for transparent, interpretable outcomes. However,…
CoGS: Model Agnostic Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, JoaquÃn Arias, Elmer Salazar +1
Machine learning models are increasingly used in critical areas such as loan approvals and hiring, yet they often function as black boxes, obscuring their decision-making processes…
CoGS: Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, JoaquÃn Arias, Elmer Salazar +1
Machine learning models are increasingly used in areas such as loan approvals and hiring, yet they often function as black boxes, obscuring their decision-making processes. Transpa…
CFGs: Causality Constrained Counterfactual Explanations using goal-directed ASP
Sopam Dasgupta, JoaquÃn Arias, Elmer Salazar +1
Machine learning models that automate decision-making are increasingly used in consequential areas such as loan approvals, pretrial bail approval, and hiring. Unfortunately, most o…