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2004.07769
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SCOUT: Self-aware Discriminant Counterfactual Explanations
Computer Vision and Pattern Recognition (CVPR), 2020
16 April 2020
Pei Wang
Nuno Vasconcelos
FAtt
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Papers citing
"SCOUT: Self-aware Discriminant Counterfactual Explanations"
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Looking in the mirror: A faithful counterfactual explanation method for interpreting deep image classification models
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Jiashu Qu
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Valentin Gerard
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Eduardo Valle
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Counterfactual Image Editing
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Elias Bareinboim
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F. Rea
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181
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Interpretable Knowledge Tracing via Response Influence-based Counterfactual Reasoning
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Minghe Yu
Bo Jiang
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Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning
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Andrea Bartos
Philipp Spitzer
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Niklas Kühl
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305
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Two-Stage Holistic and Contrastive Explanation of Image Classification
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Shijian Deng
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ML-Based Teaching Systems: A Conceptual Framework
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Niklas Kühl
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VCD: Visual Causality Discovery for Cross-Modal Question Reasoning
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Zehua Wang
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Jingzhou Luo
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Adversarial Counterfactual Visual Explanations
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Guillaume Jeanneret
Loïc Simon
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Joost van de Weijer
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On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective
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423
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Diffusion Models for Counterfactual Explanations
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Guillaume Jeanneret
Loïc Simon
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421
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Cycle-Consistent Counterfactuals by Latent Transformations
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227
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Making Heads or Tails: Towards Semantically Consistent Visual Counterfactuals
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314
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From Anecdotal Evidence to Quantitative Evaluation Methods: A Systematic Review on Evaluating Explainable AI
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Michelle Peters
Yasmin Schmitt
Jorg Schlotterer
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Nicole Meister
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Éloi Zablocki
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309
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A. S. Bates
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Long Chen
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482
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Learn-Explain-Reinforce: Counterfactual Reasoning and Its Guidance to Reinforce an Alzheimer's Disease Diagnosis Model
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272
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174
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Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models
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Yijun Li
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13 Apr 2021
ECINN: Efficient Counterfactuals from Invertible Neural Networks
British Machine Vision Conference (BMVC), 2021
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Alexandros Iosifidis
Ira Assent
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268
32
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25 Mar 2021
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