Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning

30 January 2022

Papers citing "Debiased-CAM to mitigate systematic error with faithful visual explanations of machine learning"

18 / 18 papers shown

Title
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 72 74 0 18 Jan 2021
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 47 63 0 18 Dec 2020
Concept Bottleneck Models Pang Wei Koh Thao Nguyen Y. S. Tang Stephen Mussmann Emma Pierson Been Kim Percy Liang 69 801 0 09 Jul 2020
Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance Gagan Bansal Tongshuang Wu Joyce Zhou Raymond Fok Besmira Nushi Ece Kamar Marco Tulio Ribeiro Daniel S. Weld 54 588 0 26 Jun 2020
Evaluating Saliency Map Explanations for Convolutional Neural Networks: A User Study Ahmed Alqaraawi M. Schuessler Philipp Weiß Enrico Costanza N. Bianchi-Berthouze AAML FAtt XAI 35 199 0 03 Feb 2020
"How do I fool you?": Manipulating User Trust via Misleading Black Box Explanations Himabindu Lakkaraju Osbert Bastani 37 251 0 15 Nov 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 37 329 0 19 Jun 2019
Tell Me Where to Look: Guided Attention Inference Network Kunpeng Li Ziyan Wu Kuan-Chuan Peng Jan Ernst Y. Fu 65 530 0 27 Feb 2018
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 69 3,922 0 06 Feb 2018
DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks Orest Kupyn Volodymyr Budzan Mykola Mykhailych Dmytro Mishkin Jirí Matas 3DV 49 1,457 0 19 Nov 2017
Explanation in Artificial Intelligence: Insights from the Social Sciences Tim Miller XAI 210 4,229 0 22 Jun 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 26 1,514 0 11 Apr 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 91 585 0 10 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 67 5,920 0 04 Mar 2017
Paying More Attention to Attention: Improving the Performance of Convolutional Neural Networks via Attention Transfer Sergey Zagoruyko N. Komodakis 83 2,561 0 12 Dec 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 109 9,266 0 14 Dec 2015
Microsoft COCO Captions: Data Collection and Evaluation Server Xinlei Chen Hao Fang Nayeon Lee Ramakrishna Vedantam Saurabh Gupta Piotr Dollar C. L. Zitnick 132 2,461 0 01 Apr 2015
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 178 15,825 0 12 Nov 2013