Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives

21 February 2018

Karthikeyan Shanmugam

Payel Das

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Papers citing "Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives"

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Cardinality-Minimal Explanations for Monotonic Neural Networks Ouns El Harzli Bernardo Cuenca Grau Ian Horrocks FAtt 40 5 0 19 May 2022
Sparse Visual Counterfactual Explanations in Image Space Valentyn Boreiko Maximilian Augustin Francesco Croce Philipp Berens Matthias Hein BDL CML 32 26 0 16 May 2022
Gradient-based Counterfactual Explanations using Tractable Probabilistic Models Xiaoting Shao Kristian Kersting BDL 22 1 0 16 May 2022
Diffusion Models for Counterfactual Explanations Guillaume Jeanneret Loïc Simon F. Jurie DiffM 35 55 0 29 Mar 2022
Human-Centered Concept Explanations for Neural Networks Chih-Kuan Yeh Been Kim Pradeep Ravikumar FAtt 42 26 0 25 Feb 2022
First is Better Than Last for Language Data Influence Chih-Kuan Yeh Ankur Taly Mukund Sundararajan Frederick Liu Pradeep Ravikumar TDI 34 20 0 24 Feb 2022
Holistic Adversarial Robustness of Deep Learning Models Pin-Yu Chen Sijia Liu AAML 54 16 0 15 Feb 2022
Analogies and Feature Attributions for Model Agnostic Explanation of Similarity Learners Karthikeyan N. Ramamurthy Amit Dhurandhar Dennis L. Wei Zaid Bin Tariq FAtt 45 3 0 02 Feb 2022
Which Style Makes Me Attractive? Interpretable Control Discovery and Counterfactual Explanation on StyleGAN Yangqiu Song Qiulin Wang Jiquan Pei Yu Yang Xiangyang Ji CVBM 32 3 0 24 Jan 2022
On the Robustness of Sparse Counterfactual Explanations to Adverse Perturbations M. Virgolin Saverio Fracaros CML 26 36 0 22 Jan 2022
Towards a Shapley Value Graph Framework for Medical peer-influence J. Duell M. Seisenberger Gert Aarts Shang-Ming Zhou Xiuyi Fan 21 0 0 29 Dec 2021
Towards Relatable Explainable AI with the Perceptual Process Wencan Zhang Brian Y. Lim AAML XAI 27 62 0 28 Dec 2021
Counterfactual Explanations via Latent Space Projection and Interpolation Brian Barr Matthew R. Harrington Samuel Sharpe Capital One BDL 38 10 0 02 Dec 2021
MCCE: Monte Carlo sampling of realistic counterfactual explanations Annabelle Redelmeier Martin Jullum K. Aas Anders Løland BDL 37 11 0 18 Nov 2021
Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions Prateek Yadav Peter Hase Joey Tianyi Zhou 21 11 0 01 Nov 2021
On Quantitative Evaluations of Counterfactuals Frederik Hvilshoj Alexandros Iosifidis Ira Assent 19 10 0 30 Oct 2021
Explaining Latent Representations with a Corpus of Examples Jonathan Crabbé Zhaozhi Qian F. Imrie M. Schaar FAtt 18 37 0 28 Oct 2021
Deep Neural Networks and Tabular Data: A Survey V. Borisov Tobias Leemann Kathrin Seßler Johannes Haug Martin Pawelczyk Gjergji Kasneci LMTD 49 650 0 05 Oct 2021
Generating User-Centred Explanations via Illocutionary Question Answering: From Philosophy to Interfaces Francesco Sovrano F. Vitali 48 14 0 02 Oct 2021
Designing Counterfactual Generators using Deep Model Inversion Jayaraman J. Thiagarajan V. Narayanaswamy Deepta Rajan J. Liang Akshay S. Chaudhari A. Spanias DiffM 20 22 0 29 Sep 2021
Let the CAT out of the bag: Contrastive Attributed explanations for Text Saneem A. Chemmengath A. Azad Ronny Luss Amit Dhurandhar FAtt 34 10 0 16 Sep 2021
Self-learn to Explain Siamese Networks Robustly Chao Chen Yifan Shen Guixiang Ma Xiangnan Kong S. Rangarajan Xi Zhang Sihong Xie 48 5 0 15 Sep 2021
From Heatmaps to Structural Explanations of Image Classifiers Li Fuxin Zhongang Qi Saeed Khorram Vivswan Shitole Prasad Tadepalli Minsuk Kahng Alan Fern XAI FAtt 23 4 0 13 Sep 2021
An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability Francesco Sovrano F. Vitali 42 30 0 11 Sep 2021
Unsupervised Causal Binary Concepts Discovery with VAE for Black-box Model Explanation Thien Q. Tran Kazuto Fukuchi Youhei Akimoto Jun Sakuma CML 40 10 0 09 Sep 2021
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey Richard Dazeley Peter Vamplew Francisco Cruz 32 60 0 20 Aug 2021
Uncertainty Estimation and Out-of-Distribution Detection for Counterfactual Explanations: Pitfalls and Solutions Eoin Delaney Derek Greene Mark T. Keane 27 24 0 20 Jul 2021
Contrastive Explanations for Argumentation-Based Conclusions A. Borg Floris Bex 11 7 0 07 Jul 2021
Generating Contrastive Explanations for Inductive Logic Programming Based on a Near Miss Approach Johannes Rabold M. Siebers Ute Schmid 31 14 0 15 Jun 2021
A unified logical framework for explanations in classifier systems Xinghan Liu E. Lorini 25 12 0 30 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 34 184 0 15 May 2021
Contrastive Explanations for Explaining Model Adaptations André Artelt Fabian Hinder Valerie Vaquet Robert Feldhans Barbara Hammer 57 4 0 06 Apr 2021
Local Explanations via Necessity and Sufficiency: Unifying Theory and Practice David S. Watson Limor Gultchin Ankur Taly Luciano Floridi 22 63 0 27 Mar 2021
Explaining Black-Box Algorithms Using Probabilistic Contrastive Counterfactuals Sainyam Galhotra Romila Pradhan Babak Salimi CML 24 105 0 22 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal Zifan Wang Matt Fredrikson Anupam Datta OOD FAtt 35 25 0 20 Mar 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 37 55 0 18 Mar 2021
Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties Lisa Schut Oscar Key R. McGrath Luca Costabello Bogdan Sacaleanu Medb Corcoran Y. Gal CML 26 47 0 16 Mar 2021
Explaining Network Intrusion Detection System Using Explainable AI Framework Shraddha Mane Dattaraj J. Rao AAML 33 69 0 12 Mar 2021
Counterfactual Explanations for Oblique Decision Trees: Exact, Efficient Algorithms Miguel Á. Carreira-Perpiñán Suryabhan Singh Hada CML AAML 18 33 0 01 Mar 2021
If Only We Had Better Counterfactual Explanations: Five Key Deficits to Rectify in the Evaluation of Counterfactual XAI Techniques Mark T. Keane Eoin M. Kenny Eoin Delaney Barry Smyth CML 27 146 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 67 100 0 11 Jan 2021
Towards Unifying Feature Attribution and Counterfactual Explanations: Different Means to the Same End R. Mothilal Divyat Mahajan Chenhao Tan Amit Sharma FAtt CML 27 100 0 10 Nov 2020
Explainable AI meets Healthcare: A Study on Heart Disease Dataset Devam Dave Het Naik Smiti Singhal Pankesh Patel 25 63 0 06 Nov 2020
Contrastive Graph Neural Network Explanation Lukas Faber A. K. Moghaddam Roger Wattenhofer 33 36 0 26 Oct 2020
Counterfactual Explanations and Algorithmic Recourses for Machine Learning: A Review Sahil Verma Varich Boonsanong Minh Hoang Keegan E. Hines John P. Dickerson Chirag Shah CML 26 164 0 20 Oct 2020
Explaining Chemical Toxicity using Missing Features Kar Wai Lim Bhanushee Sharma Payel Das Vijil Chenthamarakshan J. Dordick 24 7 0 23 Sep 2020
On Generating Plausible Counterfactual and Semi-Factual Explanations for Deep Learning Eoin M. Kenny Mark T. Keane 28 99 0 10 Sep 2020
PermuteAttack: Counterfactual Explanation of Machine Learning Credit Scorecards Masoud Hashemi Ali Fathi AAML 15 32 0 24 Aug 2020
Counterfactual Explanation Based on Gradual Construction for Deep Networks Hong G Jung Sin-Han Kang Hee-Dong Kim Dong-Ok Won Seong-Whan Lee OOD FAtt 25 22 0 05 Aug 2020
Sequential Explanations with Mental Model-Based Policies A. Yeung Shalmali Joshi Joseph Jay Williams Frank Rudzicz FAtt LRM 36 15 0 17 Jul 2020