Sparse Visual Counterfactual Explanations in Image Space

16 May 2022

Matthias Hein

Papers citing "Sparse Visual Counterfactual Explanations in Image Space"

50 / 55 papers shown

Title
From Visual Explanations to Counterfactual Explanations with Latent Diffusion Tung Luu Nam Le Duc Le Bac Le DiffM AAML FAtt 194 0 0 12 Apr 2025
Global Counterfactual Directions Bartlomiej Sobieski P. Biecek DiffM 77 6 0 18 Apr 2024
Discriminative Class Tokens for Text-to-Image Diffusion Models Idan Schwartz Vésteinn Snaebjarnarson Hila Chefer Ryan Cotterell Serge Belongie Lior Wolf Sagie Benaim 55 10 0 30 Mar 2023
Diffusion Causal Models for Counterfactual Estimation Pedro Sanchez Sotirios A. Tsaftaris DiffM BDL 68 72 0 21 Feb 2022
GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models Alex Nichol Prafulla Dhariwal Aditya A. Ramesh Pranav Shyam Pamela Mishkin Bob McGrew Ilya Sutskever Mark Chen 323 3,594 0 20 Dec 2021
Blended Diffusion for Text-driven Editing of Natural Images Omri Avrahami Dani Lischinski Ohad Fried DiffM 101 947 0 29 Nov 2021
Large-scale Unsupervised Semantic Segmentation Shangqi Gao Zhong-Yu Li Ming-Hsuan Yang Mingg-Ming Cheng Junwei Han Philip Torr UQCV 84 88 0 06 Jun 2021
Diffusion Models Beat GANs on Image Synthesis Prafulla Dhariwal Alex Nichol 206 7,818 0 11 May 2021
Explaining in Style: Training a GAN to explain a classifier in StyleSpace Oran Lang Yossi Gandelsman Michal Yarom Yoav Wald G. Elidan ... William T. Freeman Phillip Isola Amir Globerson Michal Irani Inbar Mosseri GAN 106 154 0 27 Apr 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 93 48 0 16 Mar 2021
Mind the box: $l_1$ -APGD for sparse adversarial attacks on image classifiers Francesco Croce Matthias Hein AAML 77 55 0 01 Mar 2021
Learning Transferable Visual Models From Natural Language Supervision Alec Radford Jong Wook Kim Chris Hallacy Aditya A. Ramesh Gabriel Goh ... Amanda Askell Pamela Mishkin Jack Clark Gretchen Krueger Ilya Sutskever CLIP VLM 871 29,341 0 26 Feb 2021
Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images K. Schutte O. Moindrot P. Hérent Jean-Baptiste Schiratti S. Jégou FAtt MedIm 109 60 0 19 Jan 2021
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 67 120 0 03 Dec 2020
Understanding Failures of Deep Networks via Robust Feature Extraction Sahil Singla Besmira Nushi S. Shah Ece Kamar Eric Horvitz FAtt 50 84 0 03 Dec 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 316 702 0 19 Oct 2020
Uncovering the Limits of Adversarial Training against Norm-Bounded Adversarial Examples Sven Gowal Chongli Qin J. Uesato Timothy A. Mann Pushmeet Kohli AAML 47 331 0 07 Oct 2020
Perceptual Adversarial Robustness: Defense Against Unseen Threat Models Cassidy Laidlaw Sahil Singla Soheil Feizi AAML OOD 86 187 0 22 Jun 2020
Deep Structural Causal Models for Tractable Counterfactual Inference Nick Pawlowski Daniel Coelho De Castro Ben Glocker CML MedIm 101 236 0 11 Jun 2020
Adversarial Robustness on In- and Out-Distribution Improves Explainability Maximilian Augustin Alexander Meinke Matthias Hein OOD 154 102 0 20 Mar 2020
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks Francesco Croce Matthias Hein AAML 213 1,842 0 03 Mar 2020
Big Transfer (BiT): General Visual Representation Learning Alexander Kolesnikov Lucas Beyer Xiaohua Zhai J. Puigcerver Jessica Yung Sylvain Gelly N. Houlsby MQ 278 1,205 0 24 Dec 2019
AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty Dan Hendrycks Norman Mu E. D. Cubuk Barret Zoph Justin Gilmer Balaji Lakshminarayanan OOD UQCV 97 1,300 0 05 Dec 2019
Self-training with Noisy Student improves ImageNet classification Qizhe Xie Minh-Thang Luong Eduard H. Hovy Quoc V. Le NoLa 304 2,386 0 11 Nov 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation Methods Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 68 817 0 06 Nov 2019
Natural Adversarial Examples Dan Hendrycks Kevin Zhao Steven Basart Jacob Steinhardt D. Song OODD 200 1,469 0 16 Jul 2019
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 81 331 0 19 Jun 2019
Unlabeled Data Improves Adversarial Robustness Y. Carmon Aditi Raghunathan Ludwig Schmidt Percy Liang John C. Duchi 121 752 0 31 May 2019
Explaining Machine Learning Classifiers through Diverse Counterfactual Explanations R. Mothilal Amit Sharma Chenhao Tan CML 106 1,018 0 19 May 2019
On the Connection Between Adversarial Robustness and Saliency Map Interpretability Christian Etmann Sebastian Lunz Peter Maass Carola-Bibiane Schönlieb AAML FAtt 58 161 0 10 May 2019
Full-Gradient Representation for Neural Network Visualization Suraj Srinivas François Fleuret MILM FAtt 70 273 0 02 May 2019
Counterfactual Visual Explanations Yash Goyal Ziyan Wu Jan Ernst Dhruv Batra Devi Parikh Stefan Lee CML 75 510 0 16 Apr 2019
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations Fred Hohman Haekyu Park Caleb Robinson Duen Horng Chau FAtt 3DH HAI 37 217 0 04 Apr 2019
Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet Wieland Brendel Matthias Bethge SSL FAtt 84 561 0 20 Mar 2019
A Frank-Wolfe Framework for Efficient and Effective Adversarial Attacks Jinghui Chen Dongruo Zhou Jinfeng Yi Quanquan Gu AAML 53 68 0 27 Nov 2018
Grounding Visual Explanations Lisa Anne Hendricks Ronghang Hu Trevor Darrell Zeynep Akata FAtt 53 227 0 25 Jul 2018
Explaining Image Classifiers by Counterfactual Generation C. Chang Elliot Creager Anna Goldenberg David Duvenaud VLM 70 264 0 20 Jul 2018
Recognition in Terra Incognita Sara Beery Grant Van Horn Pietro Perona 90 847 0 13 Jul 2018
Do CIFAR-10 Classifiers Generalize to CIFAR-10? Benjamin Recht Rebecca Roelofs Ludwig Schmidt Vaishaal Shankar OOD FedML ELM 166 409 0 01 Jun 2018
Robustness May Be at Odds with Accuracy Dimitris Tsipras Shibani Santurkar Logan Engstrom Alexander Turner Aleksander Madry AAML 99 1,778 0 30 May 2018
Explanations based on the Missing: Towards Contrastive Explanations with Pertinent Negatives Amit Dhurandhar Pin-Yu Chen Ronny Luss Chun-Chen Tu Pai-Shun Ting Karthikeyan Shanmugam Payel Das FAtt 113 589 0 21 Feb 2018
Counterfactual Explanations without Opening the Black Box: Automated Decisions and the GDPR Sandra Wachter Brent Mittelstadt Chris Russell MLAU 100 2,350 0 01 Nov 2017
Interpretation of Neural Networks is Fragile Amirata Ghorbani Abubakar Abid James Zou FAtt AAML 126 865 0 29 Oct 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 239 4,259 0 22 Jun 2017
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 301 12,060 0 19 Jun 2017
On Calibration of Modern Neural Networks Chuan Guo Geoff Pleiss Yu Sun Kilian Q. Weinberger UQCV 294 5,825 0 14 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 21,864 0 22 May 2017
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 289 19,981 0 07 Oct 2016
Generating Visual Explanations Lisa Anne Hendricks Zeynep Akata Marcus Rohrbach Jeff Donahue Bernt Schiele Trevor Darrell VLM FAtt 81 618 0 28 Mar 2016
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 354 10,180 0 16 Mar 2016