Interpreting CNNs via Decision Trees

1 February 2018

Papers citing "Interpreting CNNs via Decision Trees"

38 / 38 papers shown

Title
Safety Implications of Explainable Artificial Intelligence in End-to-End Autonomous Driving Shahin Atakishiyev Mohammad Salameh Randy Goebel 134 6 0 18 Mar 2024
Explaining Deep Convolutional Neural Networks for Image Classification by Evolving Local Interpretable Model-agnostic Explanations Bin Wang Wenbin Pei Bing Xue Mengjie Zhang FAtt 93 3 0 28 Nov 2022
Do Explanations make VQA Models more Predictable to a Human? Arjun Chandrasekaran Viraj Prabhu Deshraj Yadav Prithvijit Chattopadhyay Devi Parikh FAtt 102 97 0 29 Oct 2018
Explainable Neural Networks based on Additive Index Models J. Vaughan Agus Sudjianto Erind Brahimi Jie Chen V. Nair 32 106 0 05 Jun 2018
Unsupervised Learning of Neural Networks to Explain Neural Networks Quanshi Zhang Yu Yang Yuchen Liu Ying Nian Wu Song-Chun Zhu FAtt SSL 27 27 0 18 May 2018
Network Transplanting Quanshi Zhang Yu Yang Ying Nian Wu Song-Chun Zhu OOD 33 5 0 26 Apr 2018
Visual Interpretability for Deep Learning: a Survey Quanshi Zhang Song-Chun Zhu FaML HAI 75 812 0 02 Feb 2018
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks Ruth C. Fong Andrea Vedaldi FAtt 44 263 0 10 Jan 2018
Distilling a Neural Network Into a Soft Decision Tree Nicholas Frosst Geoffrey E. Hinton 161 635 0 27 Nov 2017
Beyond Sparsity: Tree Regularization of Deep Models for Interpretability Mike Wu M. C. Hughes S. Parbhoo Maurizio Zazzi Volker Roth Finale Doshi-Velez AI4CE 112 281 0 16 Nov 2017
Examining CNN Representations with respect to Dataset Bias Quanshi Zhang Wenguan Wang Song-Chun Zhu SSL FAtt 29 104 0 29 Oct 2017
Dynamic Routing Between Capsules S. Sabour Nicholas Frosst Geoffrey E. Hinton 88 4,584 0 26 Oct 2017
Interpretable Convolutional Neural Networks Quanshi Zhang Ying Nian Wu Song-Chun Zhu FAtt 48 774 0 02 Oct 2017
Interpreting CNN Knowledge via an Explanatory Graph Quanshi Zhang Ruiming Cao Feng Shi Ying Nian Wu Song-Chun Zhu FAtt GNN SSL 39 242 0 05 Aug 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 405 21,459 0 22 May 2017
Learning how to explain neural networks: PatternNet and PatternAttribution Pieter-Jan Kindermans Kristof T. Schütt Maximilian Alber K. Müller D. Erhan Been Kim Sven Dähne XAI FAtt 54 338 0 16 May 2017
Network Dissection: Quantifying Interpretability of Deep Visual Representations David Bau Bolei Zhou A. Khosla A. Oliva Antonio Torralba MILM FAtt 80 1,503 1 19 Apr 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 45 1,514 0 11 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 134 2,854 0 14 Mar 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 343 3,742 0 28 Feb 2017
Growing Interpretable Part Graphs on ConvNets via Multi-Shot Learning Quanshi Zhang Ruiming Cao Ying Nian Wu Song-Chun Zhu 38 70 0 14 Nov 2016
Identifying Unknown Unknowns in the Open World: Representations and Policies for Guided Exploration Himabindu Lakkaraju Ece Kamar R. Caruana Eric Horvitz 32 150 0 28 Oct 2016
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 200 19,796 0 07 Oct 2016
InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets Xi Chen Yan Duan Rein Houthooft John Schulman Ilya Sutskever Pieter Abbeel GAN 138 4,224 0 12 Jun 2016
The Mythos of Model Interpretability Zachary Chase Lipton FaML 110 3,672 0 10 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 478 16,765 0 16 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.3K 192,638 0 10 Dec 2015
Inverting Visual Representations with Convolutional Networks Alexey Dosovitskiy Thomas Brox SSL FAtt 54 662 0 09 Jun 2015
Understanding deep features with computer-generated imagery Mathieu Aubry Bryan C. Russell 37 148 0 03 Jun 2015
Neural Activation Constellations: Unsupervised Part Model Discovery with Convolutional Networks Marcel Simon E. Rodner 54 412 0 30 Apr 2015
Object Detectors Emerge in Deep Scene CNNs Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba ObjD 110 1,279 0 22 Dec 2014
Understanding Deep Image Representations by Inverting Them Aravindh Mahendran Andrea Vedaldi FAtt 86 1,959 0 26 Nov 2014
Part Detector Discovery in Deep Convolutional Neural Networks Marcel Simon E. Rodner Joachim Denzler ObjD 39 76 0 12 Nov 2014
How transferable are features in deep neural networks? J. Yosinski Jeff Clune Yoshua Bengio Hod Lipson OOD 123 8,309 0 06 Nov 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 822 99,991 0 04 Sep 2014
Detect What You Can: Detecting and Representing Objects using Holistic Models and Body Parts Xianjie Chen Roozbeh Mottaghi Xiaobai Liu Sanja Fidler R. Urtasun Alan Yuille 57 639 0 08 Jun 2014
Intriguing properties of neural networks Christian Szegedy Wojciech Zaremba Ilya Sutskever Joan Bruna D. Erhan Ian Goodfellow Rob Fergus AAML 159 14,831 1 21 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 258 15,825 0 12 Nov 2013