Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers

6 December 2019

Papers citing "Preserving Causal Constraints in Counterfactual Explanations for Machine Learning Classifiers"

50 / 50 papers shown

Title
Understanding Fixed Predictions via Confined Regions Connor Lawless Tsui-Wei Weng Berk Ustun Madeleine Udell 48 0 0 22 Feb 2025
Explaining the Behavior of Black-Box Prediction Algorithms with Causal Learning Numair Sani Daniel Malinsky I. Shpitser CML 79 15 0 10 Jan 2025
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit Junyu Cao Ruijiang Gao Esmaeil Keyvanshokooh 37 1 0 18 Oct 2024
Probabilistically Plausible Counterfactual Explanations with Normalizing Flows Patryk Wielopolski Oleksii Furman Jerzy Stefanowski Maciej Ziȩba 43 2 0 27 May 2024
Trustworthy Actionable Perturbations Jesse Friedbaum S. Adiga Ravi Tandon AAML 38 2 0 18 May 2024
CountARFactuals -- Generating plausible model-agnostic counterfactual explanations with adversarial random forests Susanne Dandl Kristin Blesch Timo Freiesleben Gunnar Konig Jan Kapar B. Bischl Marvin N. Wright AAML 32 5 0 04 Apr 2024
Generating Likely Counterfactuals Using Sum-Product Networks Jiri Nemecek Tomás Pevný Jakub Marecek TPM 76 0 0 25 Jan 2024
Counterfactual Explanation Policies in RL Shripad Deshmukh R Srivatsan Supriti Vijay Jayakumar Subramanian Chirag Agarwal OffRL 35 0 0 25 Jul 2023
Explainable Predictive Maintenance Sepideh Pashami Sławomir Nowaczyk Yuantao Fan Jakub Jakubowski Nuno Paiva ... Bruno Veloso M. Sayed-Mouchaweh L. Rajaoarisoa Grzegorz J. Nalepa João Gama 32 8 0 08 Jun 2023
GLOBE-CE: A Translation-Based Approach for Global Counterfactual Explanations Dan Ley Saumitra Mishra Daniele Magazzeni LRM 38 16 0 26 May 2023
counterfactuals: An R Package for Counterfactual Explanation Methods Susanne Dandl Andreas Hofheinz Martin Binder B. Bischl Giuseppe Casalicchio 31 2 0 13 Apr 2023
CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data using Normalizing Flows Tri Dung Duong Qian Li Guandong Xu OOD 37 7 0 26 Mar 2023
Towards Learning and Explaining Indirect Causal Effects in Neural Networks Abbaavaram Gowtham Reddy Saketh Bachu Harsh Nilesh Pathak Ben Godfrey V. Balasubramanian V. Varshaneya Satya Narayanan Kar CML 31 0 0 24 Mar 2023
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 40 3 0 07 Feb 2023
Finding Regions of Counterfactual Explanations via Robust Optimization Donato Maragno Jannis Kurtz Tabea E. Rober Rob Goedhart cS. .Ilker Birbil D. Hertog 49 21 0 26 Jan 2023
Evaluating counterfactual explanations using Pearl's counterfactual method Bevan I. Smith CML 22 1 0 06 Jan 2023
Decomposing Counterfactual Explanations for Consequential Decision Making Martin Pawelczyk Lea Tiyavorabun Gjergji Kasneci CML 21 1 0 03 Nov 2022
Backtracking Counterfactuals Julius von Kügelgen Abdirisak Mohamed Sander Beckers LRM 43 16 0 01 Nov 2022
Improvement-Focused Causal Recourse (ICR) Gunnar Konig Timo Freiesleben Moritz Grosse-Wentrup CML 31 15 0 27 Oct 2022
Redefining Counterfactual Explanations for Reinforcement Learning: Overview, Challenges and Opportunities Jasmina Gajcin Ivana Dusparic CML OffRL 35 8 0 21 Oct 2022
CLEAR: Generative Counterfactual Explanations on Graphs Jing Ma Ruocheng Guo Saumitra Mishra Aidong Zhang Jundong Li CML OOD 35 53 0 16 Oct 2022
Counterfactual Explanations Using Optimization With Constraint Learning Donato Maragno Tabea E. Rober Ilker Birbil CML 58 10 0 22 Sep 2022
MACE: An Efficient Model-Agnostic Framework for Counterfactual Explanation Wenzhuo Yang Jia Li Caiming Xiong S. Hoi CML 35 13 0 31 May 2022
Features of Explainability: How users understand counterfactual and causal explanations for categorical and continuous features in XAI Greta Warren Mark T. Keane R. Byrne CML 27 22 0 21 Apr 2022
Probabilistically Robust Recourse: Navigating the Trade-offs between Costs and Robustness in Algorithmic Recourse Martin Pawelczyk Teresa Datta Johannes van-den-Heuvel Gjergji Kasneci Himabindu Lakkaraju 24 38 0 13 Mar 2022
LIMREF: Local Interpretable Model Agnostic Rule-based Explanations for Forecasting, with an Application to Electricity Smart Meter Data Dilini Sewwandi Rajapaksha Christoph Bergmeir AI4TS 14 16 0 15 Feb 2022
Causal Explanations and XAI Sander Beckers CML XAI 26 34 0 31 Jan 2022
Counterfactual Explanations via Latent Space Projection and Interpolation Brian Barr Matthew R. Harrington Samuel Sharpe Capital One BDL 33 10 0 02 Dec 2021
On Quantitative Evaluations of Counterfactuals Frederik Hvilshoj Alexandros Iosifidis Ira Assent 19 10 0 30 Oct 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 27 647 0 05 Oct 2021
Model Explanations via the Axiomatic Causal Lens Gagan Biradar Vignesh Viswanathan Yair Zick XAI CML 25 1 0 08 Sep 2021
Longitudinal Distance: Towards Accountable Instance Attribution Rosina O. Weber Prateek Goel S. Amiri G. Simpson 16 0 0 23 Aug 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data Raphael Mazzine David Martens 32 33 0 09 Jul 2021
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 24 26 0 29 Jun 2021
How Well do Feature Visualizations Support Causal Understanding of CNN Activations? Roland S. Zimmermann Judy Borowski Robert Geirhos Matthias Bethge Thomas S. A. Wallis Wieland Brendel FAtt 44 31 0 23 Jun 2021
Algorithmic Recourse in Partially and Fully Confounded Settings Through Bounding Counterfactual Effects Julius von Kügelgen N. Agarwal Jakob Zeitler Afsaneh Mastouri Bernhard Schölkopf CML 17 2 0 22 Jun 2021
Rational Shapley Values David S. Watson 23 20 0 18 Jun 2021
Optimal Counterfactual Explanations in Tree Ensembles Axel Parmentier Thibaut Vidal 19 54 0 11 Jun 2021
Consequence-aware Sequential Counterfactual Generation Philip Naumann Eirini Ntoutsi OffRL 17 24 0 12 Apr 2021
Towards Robust and Reliable Algorithmic Recourse Sohini Upadhyay Shalmali Joshi Himabindu Lakkaraju 25 108 0 26 Feb 2021
Explaining the Black-box Smoothly- A Counterfactual Approach Junyu Chen Yong Du Yufan He W. Paul Segars Ye Li MedIm FAtt 65 100 0 11 Jan 2021
GeCo: Quality Counterfactual Explanations in Real Time Maximilian Schleich Zixuan Geng Yihong Zhang D. Suciu 46 61 0 05 Jan 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 28 119 0 03 Dec 2020
A Series of Unfortunate Counterfactual Events: the Role of Time in Counterfactual Explanations Andrea Ferrario M. Loi 22 5 0 09 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 35 62 0 11 Sep 2020
On Counterfactual Explanations under Predictive Multiplicity Martin Pawelczyk Klaus Broelemann Gjergji Kasneci 25 85 0 23 Jun 2020
Algorithmic recourse under imperfect causal knowledge: a probabilistic approach Amir-Hossein Karimi Julius von Kügelgen Bernhard Schölkopf Isabel Valera CML 28 178 0 11 Jun 2020
Algorithmic Recourse: from Counterfactual Explanations to Interventions Amir-Hossein Karimi Bernhard Schölkopf Isabel Valera CML 24 337 0 14 Feb 2020
Asymmetric Shapley values: incorporating causal knowledge into model-agnostic explainability Christopher Frye C. Rowat Ilya Feige 16 180 0 14 Oct 2019
Explaining Visual Models by Causal Attribution Álvaro Parafita Jordi Vitrià CML FAtt 62 35 0 19 Sep 2019