Multi-Objective Counterfactual Explanations

23 April 2020

Papers citing "Multi-Objective Counterfactual Explanations"

47 / 47 papers shown

Title
Why Are You Wrong? Counterfactual Explanations for Language Grounding with 3D Objects Tobias Preintner Weixuan Yuan Qi Huang Adrian König Thomas Bäck E. Raponi N. V. Stein 29 0 0 09 May 2025
DiCE-Extended: A Robust Approach to Counterfactual Explanations in Machine Learning Volkan Bakir Polat Goktas Sureyya Akyuz 50 0 0 26 Apr 2025
Graph Counterfactual Explainable AI via Latent Space Traversal Andreas Abildtrup Hansen Paraskevas Pegios Anna Calissano Aasa Feragen OOD BDL AAML 83 0 0 15 Jan 2025
Robust Counterfactual Explanations under Model Multiplicity Using Multi-Objective Optimization Keita Kinjo 34 1 0 10 Jan 2025
HR-Bandit: Human-AI Collaborated Linear Recourse Bandit Junyu Cao Ruijiang Gao Esmaeil Keyvanshokooh 37 1 0 18 Oct 2024
Counterfactual Metarules for Local and Global Recourse Tom Bewley Salim I. Amoukou Saumitra Mishra Daniele Magazzeni Manuela Veloso 42 1 0 29 May 2024
Trustworthy Actionable Perturbations Jesse Friedbaum S. Adiga Ravi Tandon AAML 38 2 0 18 May 2024
Learning Actionable Counterfactual Explanations in Large State Spaces Keziah Naggita Matthew R. Walter Avrim Blum OffRL 33 0 0 25 Apr 2024
Generating Counterfactual Trajectories with Latent Diffusion Models for Concept Discovery Payal Varshney Adriano Lucieri Christoph Balada Andreas Dengel Sheraz Ahmed MedIm DiffM 46 4 0 16 Apr 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
Even-Ifs From If-Onlys: Are the Best Semi-Factual Explanations Found Using Counterfactuals As Guides? Saugat Aryal Mark T. Keane 32 4 0 01 Mar 2024
On the Relationship Between Interpretability and Explainability in Machine Learning Benjamin Leblanc Pascal Germain FaML 26 0 0 20 Nov 2023
Finding Optimal Diverse Feature Sets with Alternative Feature Selection Jakob Bach 15 1 0 21 Jul 2023
On the Connection between Game-Theoretic Feature Attributions and Counterfactual Explanations Emanuele Albini Shubham Sharma Saumitra Mishra Danial Dervovic Daniele Magazzeni FAtt 46 2 0 13 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
BELLA: Black box model Explanations by Local Linear Approximations N. Radulovic Albert Bifet Fabian M. Suchanek FAtt 31 1 0 18 May 2023
counterfactuals: An R Package for Counterfactual Explanation Methods Susanne Dandl Andreas Hofheinz Martin Binder B. Bischl Giuseppe Casalicchio 26 2 0 13 Apr 2023
Counterfactual Explanations of Neural Network-Generated Response Curves Giorgio Morales John W. Sheppard 14 1 0 08 Apr 2023
CeFlow: A Robust and Efficient Counterfactual Explanation Framework for Tabular Data using Normalizing Flows Tri Dung Duong Qian Li Guandong Xu OOD 32 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 26 0 0 24 Mar 2023
Explaining Groups of Instances Counterfactually for XAI: A Use Case, Algorithm and User Study for Group-Counterfactuals Greta Warren Markt. Keane Christophe Guéret Eoin Delaney 26 13 0 16 Mar 2023
RACCER: Towards Reachable and Certain Counterfactual Explanations for Reinforcement Learning Jasmina Gajcin Ivana Dusparic CML 24 3 0 08 Mar 2023
Finding Regions of Counterfactual Explanations via Robust Optimization Donato Maragno Jannis Kurtz Tabea E. Rober Rob Goedhart cS. .Ilker Birbil D. Hertog 44 21 0 26 Jan 2023
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 30 53 0 16 Oct 2022
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification Adrien Bennetot Gianni Franchi Javier Del Ser Raja Chatila Natalia Díaz Rodríguez AAML 25 29 0 26 Sep 2022
Attribution-based Explanations that Provide Recourse Cannot be Robust H. Fokkema R. D. Heide T. Erven FAtt 44 18 0 31 May 2022
Keep Your Friends Close and Your Counterfactuals Closer: Improved Learning From Closest Rather Than Plausible Counterfactual Explanations in an Abstract Setting Ulrike Kuhl André Artelt Barbara Hammer 32 24 0 11 May 2022
Let's Go to the Alien Zoo: Introducing an Experimental Framework to Study Usability of Counterfactual Explanations for Machine Learning Ulrike Kuhl André Artelt Barbara Hammer 27 17 0 06 May 2022
Less is More: A Call to Focus on Simpler Models in Genetic Programming for Interpretable Machine Learning M. Virgolin Eric Medvet T. Alderliesten Peter A. N. Bosman 14 6 0 05 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 19 38 0 13 Mar 2022
Evaluating Feature Attribution Methods in the Image Domain Arne Gevaert Axel-Jan Rousseau Thijs Becker D. Valkenborg T. D. Bie Yvan Saeys FAtt 21 22 0 22 Feb 2022
Counterfactual Plans under Distributional Ambiguity N. Bui D. Nguyen Viet Anh Nguyen 56 24 0 29 Jan 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 26 36 0 22 Jan 2022
Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis Giovanni De Toni Bruno Lepri Andrea Passerini CML 25 13 0 18 Jan 2022
Efficient Decompositional Rule Extraction for Deep Neural Networks Mateo Espinosa Zarlenga Z. Shams M. Jamnik 14 16 0 24 Nov 2021
Solving the Class Imbalance Problem Using a Counterfactual Method for Data Augmentation M. Temraz Markt. Keane 21 42 0 05 Nov 2021
A Survey on the Robustness of Feature Importance and Counterfactual Explanations Saumitra Mishra Sanghamitra Dutta Jason Long Daniele Magazzeni AAML 9 58 0 30 Oct 2021
Counterfactual Shapley Additive Explanations Emanuele Albini Jason Long Danial Dervovic Daniele Magazzeni 26 49 0 27 Oct 2021
A Causal Perspective on Meaningful and Robust Algorithmic Recourse Gunnar Konig Timo Freiesleben Moritz Grosse-Wentrup 27 16 0 16 Jul 2021
Counterfactual Explanations for Arbitrary Regression Models Thomas Spooner Danial Dervovic Jason Long Jon Shepard Jiahao Chen Daniele Magazzeni 19 26 0 29 Jun 2021
Consequence-aware Sequential Counterfactual Generation Philip Naumann Eirini Ntoutsi OffRL 17 24 0 12 Apr 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 42 176 0 07 Mar 2021
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 15 397 0 19 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 27 62 0 11 Sep 2020
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models Christoph Molnar Gunnar Konig J. Herbinger Timo Freiesleben Susanne Dandl Christian A. Scholbeck Giuseppe Casalicchio Moritz Grosse-Wentrup B. Bischl FAtt AI4CE 11 135 0 08 Jul 2020
Counterfactual explanation of machine learning survival models M. Kovalev Lev V. Utkin CML OffRL 24 19 0 26 Jun 2020