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Counterfactual explanations have emerged as a promising method for elucidating the behavior of opaque black-box models.
WordNet: a lexical database for English
George A. Miller · 1995
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Automated Flower Classification over a Large Number of Classes
Maria-Elena Nilsback and Andrew Zisserman · 2008
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ImageNet: A Large-Scale Hierarchical Image Database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Visualizing Higher-Layer Features of a Deep Network
Dumitru Erhan, Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2009
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Cats And Dogs
Omkar M Parkhi, Andrea Vedaldi, Andrew Zisserman, and CV Jawahar · 2012
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling · 2014
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Stochastic Backpropagation and Approximate Inference in Deep Generative Models
Danilo Jimenez Rezende, Shakir Mohamed, and Daan Wierstra · 2014
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Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2014
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On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation
Sebastian Bach, Alexander Binder, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller, and Wojciech Samek · 2015
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Variational Inference with Normalizing Flows
Danilo Rezende and Shakir Mohamed · 2015
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U-Net: Convolutional Networks for Biomedical Image Segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Rethinking the Inception Architecture for Computer Vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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TorchVision: PyTorch’s Computer Vision library
TorchVision maintainers and contributors · 2016
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Network Dissection: Quantifying Interpretability of Deep Visual Representations
David Bau, Bolei Zhou, Aditya Khosla, Aude Oliva, and Antonio Torralba · 2017
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GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Densely Connected Convolutional Networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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A Unified Approach to Interpreting Model Predictions
Scott M Lundberg and Su-In Lee · 2017
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Feature Visualization
Chris Olah, Alexander Mordvintsev, and Ludwig Schubert · 2017
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Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R Selvaraju, Michael Cogswell, Abhishek Das, Ramakrishna Vedantam, Devi Parikh, and Dhruv Batra · 2017
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Counterfactual Explanations Without Opening the Black Box: Automated Decisions and the GDPR
Sandra Wachter, Brent Mittelstadt, and Chris Russell · 2017
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VGGFace2: A Dataset for recognising faces across pose and age
Qiong Cao, Li Shen, Weidi Xie, Omkar M Parkhi, and Andrew Zisserman · 2018
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Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)
Been Kim, Martin Wattenberg, Justin Gilmer, Carrie Cai, James Wexler, Fernanda Viegas, et al · 2018
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ExplainGAN: Model Explanation via Decision Boundary Crossing Transformations
Pouya Samangouei, Ardavan Saeedi, Liam Nakagawa, and Nathan Silberman · 2018
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Approximating CNNs with Bag-of-local-Features models works surprisingly well on ImageNet
Wieland Brendel and Matthias Bethge · 2019
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This Looks Like That: Deep Learning for Interpretable Image Recognition
Chaofan Chen, Oscar Li, Daniel Tao, Alina Barnett, Cynthia Rudin, and Jonathan K Su · 2019
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Counterfactual Visual Explanations
Yash Goyal, Ziyan Wu, Jan Ernst, Dhruv Batra, Devi Parikh, and Stefan Lee · 2019
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Decoupled Weight Decay Regularization
Ilya Loshchilov and Frank Hutter · 2019
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Image Synthesis with a Single (Robust) Classifier
Shibani Santurkar, Andrew Ilyas, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry · 2019
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Generative Modeling by Estimating Gradients of the Data Distribution
Yang Song and Stefano Ermon · 2019
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CoCoX: Generating Conceptual and Counterfactual Explanations via Fault-Lines
Arjun Akula, Shuai Wang, and Song-Chun Zhu · 2020
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Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI
Alejandro Barredo Arrieta, Natalia Díaz-Rodríguez, Javier Del Ser, Adrien Bennetot, Siham Tabik, Alberto Barbado, Salvador García, Sergio Gil-López, Daniel Molina, Richard Benjamins, et al · 2020
Interpretable Counterfactual Explanations Guided by Prototypes
Arnaud Van Looveren and Janis Klaise · 2021
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IMAGINE: Image Synthesis by Image-Guided Model Inversion
Pei Wang, Yijun Li, Krishna Kumar Singh, Jingwan Lu, and Nuno Vasconcelos · 2021
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Diffusion Visual Counterfactual Explanations
Maximilian Augustin, Valentyn Boreiko, Francesco Croce, and Matthias Hein · 2022
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Blended diffusion for text-driven editing of natural images
Omri Avrahami, Dani Lischinski, and Ohad Fried · 2022
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B-cos Networks: Alignment is All We Need for Interpretability
Moritz Böhle, Mario Fritz, and Bernt Schiele · 2022
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Sparse Visual Counterfactual Explanations in Image Space
Valentyn Boreiko, Maximilian Augustin, Francesco Croce, Philipp Berens, and Matthias Hein · 2022
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Language Models are Few-Shot Learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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Generative adversarial networks
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2020
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Denoising Diffusion Probabilistic Models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Concept Bottleneck Models
Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, and Percy Liang · 2020
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MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
Cheng-Han Lee, Ziwei Liu, Lingyun Wu, and Ping Luo · 2020
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Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Reproducible scaling laws for contrastive language-image learning
Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, and Jenia Jitsev · 2022
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FLASHATTENTION: Fast and Memory-Efficient Exact Attention with IO-Awareness
Tri Dao, Dan Fu, Stefano Ermon, Atri Rudra, and Christopher Ré · 2022
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Classifier-Free Diffusion Guidance
Jonathan Ho and Tim Salimans · 2022
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STEEX: Steering Counterfactual Explanations with Semantics
Paul Jacob, Éloi Zablocki, Hédi Ben-Younes, Mickaël Chen, Patrick Pérez, and Matthieu Cord · 2022
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Diffusion Models for Counterfactual Explanations
Guillaume Jeanneret, Loïc Simon, and Frédéric Jurie · 2022
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Cycle-Consistent Counterfactuals by Latent Transformations
Saeed Khorram and Li Fuxin · 2022
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High-Resolution Image Synthesis with Latent Diffusion Models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Progressive Distillation for Fast Sampling of Diffusion Models
Tim Salimans and Jonathan Ho · 2022
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Diffusion Causal Models for Counterfactual Estimation
Pedro Sanchez and Sotirios A. Tsaftaris · 2022
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Making Heads or Tails: Towards Semantically Consistent Visual Counterfactuals
Simon Vandenhende, Dhruv Mahajan, Filip Radenovic, and Deepti Ghadiyaram · 2022
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Universal guidance for diffusion models
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2023
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Easily accessible text-to-image generation amplifies demographic stereotypes at large scale
Federico Bianchi, Pratyusha Kalluri, Esin Durmus, Faisal Ladhak, Myra Cheng, Debora Nozza, Tatsunori Hashimoto, Dan Jurafsky, James Zou, and Aylin Caliskan · 2023
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Token Merging: Your ViT But Faster
Daniel Bolya, Cheng-Yang Fu, Xiaoliang Dai, Peizhao Zhang, Christoph Feichtenhofer, and Judy Hoffman · 2023
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InstructPix2Pix: Learning to Follow Image Editing Instructions
Tim Brooks, Aleksander Holynski, and Alexei A. Efros · 2023
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Prompt-to-Prompt Image Editing with Cross-Attention Control
Amir Hertz, Ron Mokady, Jay Tenenbaum, Kfir Aberman, Yael Pritch, and Daniel Cohen-or · 2023
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Adversarial Counterfactual Visual Explanations
Guillaume Jeanneret, Loïc Simon, and Frédéric Jurie · 2023
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Stable Bias: Analyzing Societal Representations in Diffusion Models
Alexandra Sasha Luccioni, Christopher Akiki, Margaret Mitchell, and Yacine Jernite · 2023
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On Distillation of Guided Diffusion Models
Chenlin Meng, Ruiqi Gao, Diederik P Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans · 2023
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Consistency Models
Yang Song, Prafulla Dhariwal, Mark Chen, and Ilya Sutskever · 2023
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End-to-End Diffusion Latent Optimization Improves Classifier Guidance
Bram Wallace, Akash Gokul, Stefano Ermon, and Nikhil Naik · 2023
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