Explaining Image Classifiers by Counterfactual Generation

20 July 2018

Papers citing "Explaining Image Classifiers by Counterfactual Generation"

50 / 85 papers shown

Title
Faithful Counterfactual Visual Explanations (FCVE) Bismillah Khan Syed Ali Tariq Tehseen Zia Muhammad Ahsan David Windridge 44 0 0 12 Jan 2025
Reconciling Privacy and Explainability in High-Stakes: A Systematic Inquiry Supriya Manna Niladri Sett 189 0 0 30 Dec 2024
Benchmarking the Attribution Quality of Vision Models Robin Hesse Simone Schaub-Meyer Stefan Roth FAtt 39 3 0 16 Jul 2024
Inpainting the Gaps: A Novel Framework for Evaluating Explanation Methods in Vision Transformers Lokesh Badisa Sumohana S. Channappayya 45 0 0 17 Jun 2024
Listenable Maps for Zero-Shot Audio Classifiers Francesco Paissan Luca Della Libera Mirco Ravanelli Cem Subakan 40 4 0 27 May 2024
Manifold-based Shapley for SAR Recognization Network Explanation Xuran Hu Mingzhe Zhu Yuanjing Liu Zhenpeng Feng Ljubiša Stanković FAtt GAN 20 3 0 06 Jan 2024
Explaining high-dimensional text classifiers Odelia Melamed Rich Caruana 23 0 0 22 Nov 2023
Impact of architecture on robustness and interpretability of multispectral deep neural networks Charles Godfrey Elise Bishoff Myles Mckay E. Byler 34 0 0 21 Sep 2023
FunnyBirds: A Synthetic Vision Dataset for a Part-Based Analysis of Explainable AI Methods Robin Hesse Simone Schaub-Meyer Stefan Roth AAML 37 33 0 11 Aug 2023
Active Globally Explainable Learning for Medical Images via Class Association Embedding and Cyclic Adversarial Generation Ruitao Xie Jingbang Chen Limai Jiang Ru Xiao Yi-Lun Pan Yunpeng Cai GAN MedIm 27 0 0 12 Jun 2023
Reason to explain: Interactive contrastive explanations (REASONX) Laura State Salvatore Ruggieri Franco Turini LRM 30 1 0 29 May 2023
Rectifying Group Irregularities in Explanations for Distribution Shift Adam Stein Yinjun Wu Eric Wong Mayur Naik 39 1 0 25 May 2023
DEGREE: Decomposition Based Explanation For Graph Neural Networks Qizhang Feng Ninghao Liu Fan Yang Ruixiang Tang Mengnan Du Xia Hu 30 22 0 22 May 2023
A Lifted Bregman Formulation for the Inversion of Deep Neural Networks Xiaoyu Wang Martin Benning 36 2 0 01 Mar 2023
Neural Insights for Digital Marketing Content Design F. Kong Yuan Li Houssam Nassif Tanner Fiez Ricardo Henao Shreya Chakrabarti 3DV 27 10 0 02 Feb 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 41 22 0 17 Jan 2023
Explainability and Robustness of Deep Visual Classification Models Jindong Gu AAML 47 2 0 03 Jan 2023
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ Eoin Delaney A. Pakrashi Derek Greene Markt. Keane 37 16 0 16 Dec 2022
Explainability as statistical inference Hugo Senetaire Damien Garreau J. Frellsen Pierre-Alexandre Mattei FAtt 23 4 0 06 Dec 2022
OCTET: Object-aware Counterfactual Explanations Mehdi Zemni Mickaël Chen Éloi Zablocki H. Ben-younes Patrick Pérez Matthieu Cord AAML 29 29 0 22 Nov 2022
Clarity: an improved gradient method for producing quality visual counterfactual explanations Claire Theobald Frédéric Pennerath Brieuc Conan-Guez Miguel Couceiro Amedeo Napoli BDL 41 0 0 22 Nov 2022
Explaining Image Classifiers with Multiscale Directional Image Representation Stefan Kolek Robert Windesheim Héctor Andrade-Loarca Gitta Kutyniok Ron Levie 29 4 0 22 Nov 2022
Data-Centric Debugging: mitigating model failures via targeted data collection Sahil Singla Atoosa Malemir Chegini Mazda Moayeri Soheil Feiz 27 4 0 17 Nov 2022
New Definitions and Evaluations for Saliency Methods: Staying Intrinsic, Complete and Sound Arushi Gupta Nikunj Saunshi Dingli Yu Kaifeng Lyu Sanjeev Arora AAML FAtt XAI 31 6 0 05 Nov 2022
A Regularized Conditional GAN for Posterior Sampling in Image Recovery Problems Matthew Bendel Rizwan Ahmad Philip Schniter MedIm 37 5 0 24 Oct 2022
Diffusion Visual Counterfactual Explanations Maximilian Augustin Valentyn Boreiko Francesco Croce Matthias Hein DiffM BDL 32 68 0 21 Oct 2022
Shap-CAM: Visual Explanations for Convolutional Neural Networks based on Shapley Value Quan Zheng Ziwei Wang Jie Zhou Jiwen Lu FAtt 33 31 0 07 Aug 2022
Unit Testing for Concepts in Neural Networks Charles Lovering Ellie Pavlick 25 28 0 28 Jul 2022
Towards Counterfactual Image Manipulation via CLIP Yingchen Yu Fangneng Zhan Rongliang Wu Jiahui Zhang Shijian Lu Miaomiao Cui Xuansong Xie Xiansheng Hua Chunyan Miao CLIP 59 30 0 06 Jul 2022
GLANCE: Global to Local Architecture-Neutral Concept-based Explanations Avinash Kori Ben Glocker Francesca Toni 32 6 0 05 Jul 2022
Hierarchical Symbolic Reasoning in Hyperbolic Space for Deep Discriminative Models Ainkaran Santhirasekaram Avinash Kori A. Rockall Mathias Winkler Francesca Toni Ben Glocker FAtt 42 4 0 05 Jul 2022
Distilling Model Failures as Directions in Latent Space Saachi Jain Hannah Lawrence Ankur Moitra A. Madry 23 90 0 29 Jun 2022
What You See is What You Classify: Black Box Attributions Steven Stalder Nathanael Perraudin R. Achanta Fernando Perez-Cruz Michele Volpi FAtt 34 9 0 23 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
Discovering and Explaining the Representation Bottleneck of Graph Neural Networks from Multi-order Interactions Fang Wu Siyuan Li Lirong Wu Dragomir R. Radev Stan Z. Li 27 2 0 15 May 2022
Necessity and Sufficiency for Explaining Text Classifiers: A Case Study in Hate Speech Detection Esma Balkir I. Nejadgholi Kathleen C. Fraser S. Kiritchenko FAtt 41 27 0 06 May 2022
Do Users Benefit From Interpretable Vision? A User Study, Baseline, And Dataset Leon Sixt M. Schuessler Oana-Iuliana Popescu Philipp Weiß Tim Landgraf FAtt 34 14 0 25 Apr 2022
Reliable Visualization for Deep Speaker Recognition Pengqi Li Lantian Li A. Hamdulla Dong Wang HAI 40 9 0 08 Apr 2022
Human-Centered Concept Explanations for Neural Networks Chih-Kuan Yeh Been Kim Pradeep Ravikumar FAtt 42 26 0 25 Feb 2022
Vision Checklist: Towards Testable Error Analysis of Image Models to Help System Designers Interrogate Model Capabilities Xin Du Bénédicte Legastelois B. Ganesh A. Rajan Hana Chockler Vaishak Belle Stuart Anderson S. Ramamoorthy AAML 27 6 0 27 Jan 2022
Deconfounding to Explanation Evaluation in Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Xia Hu Fuli Feng Xiangnan He Tat-Seng Chua FAtt CML 17 14 0 21 Jan 2022
On Causally Disentangled Representations Abbavaram Gowtham Reddy Benin Godfrey L V. Balasubramanian OOD CML 36 21 0 10 Dec 2021
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View Di Jin Elena Sergeeva W. Weng Geeticka Chauhan Peter Szolovits OOD 56 55 0 05 Dec 2021
STEEX: Steering Counterfactual Explanations with Semantics P. Jacob Éloi Zablocki H. Ben-younes Mickaël Chen P. Pérez Matthieu Cord 19 43 0 17 Nov 2021
On Quantitative Evaluations of Counterfactuals Frederik Hvilshoj Alexandros Iosifidis Ira Assent 19 10 0 30 Oct 2021
Double Trouble: How to not explain a text classifier's decisions using counterfactuals synthesized by masked language models? Thang M. Pham Trung H. Bui Long Mai Anh Totti Nguyen 21 7 0 22 Oct 2021
A Rate-Distortion Framework for Explaining Black-box Model Decisions Stefan Kolek Duc Anh Nguyen Ron Levie Joan Bruna Gitta Kutyniok 35 15 0 12 Oct 2021
Cartoon Explanations of Image Classifiers Stefan Kolek Duc Anh Nguyen Ron Levie Joan Bruna Gitta Kutyniok FAtt 38 15 0 07 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