Concept Whitening for Interpretable Image Recognition

5 February 2020

Zhi Chen

Papers citing "Concept Whitening for Interpretable Image Recognition"

39 / 189 papers shown

Title
Acquisition of Chess Knowledge in AlphaZero Thomas McGrath A. Kapishnikov Nenad Tomašev Adam Pearce Demis Hassabis Been Kim Ulrich Paquet Vladimir Kramnik 20 158 0 17 Nov 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 15 301 0 01 Nov 2021
Knowledge-driven Active Learning Gabriele Ciravegna F. Precioso Alessandro Betti Kevin Mottin Marco Gori 8 2 0 15 Oct 2021
Toward a Unified Framework for Debugging Concept-based Models A. Bontempelli Fausto Giunchiglia Andrea Passerini Stefano Teso 20 4 0 23 Sep 2021
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation Srishti Gautam Marina M.-C. Höhne Stine Hansen Robert Jenssen Michael C. Kampffmeyer 24 49 0 27 Aug 2021
A Framework for Learning Ante-hoc Explainable Models via Concepts Anirban Sarkar Deepak Vijaykeerthy Anindya Sarkar V. Balasubramanian LRM BDL 19 46 0 25 Aug 2021
ProtoMIL: Multiple Instance Learning with Prototypical Parts for Whole-Slide Image Classification Dawid Rymarczyk Adam Pardyl Jaroslaw Kraus Aneta Kaczyńska M. Skomorowski Bartosz Zieliñski 17 21 0 24 Aug 2021
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks Lucie Charlotte Magister Dmitry Kazhdan Vikash Singh Pietro Lió 27 48 0 25 Jul 2021
Responsible and Regulatory Conform Machine Learning for Medicine: A Survey of Challenges and Solutions Eike Petersen Yannik Potdevin Esfandiar Mohammadi Stephan Zidowitz Sabrina Breyer ... Sandra Henn Ludwig Pechmann M. Leucker P. Rostalski Christian Herzog FaML AILaw OOD 27 21 0 20 Jul 2021
Algorithmic Concept-based Explainable Reasoning Dobrik Georgiev Pietro Barbiero Dmitry Kazhdan Petar Velivcković Pietro Lió 72 16 0 15 Jul 2021
Interpretable Mammographic Image Classification using Case-Based Reasoning and Deep Learning A. Barnett F. Schwartz Chaofan Tao Chaofan Chen Yinhao Ren J. Lo Cynthia Rudin 62 21 0 12 Jul 2021
When and How to Fool Explainable Models (and Humans) with Adversarial Examples Jon Vadillo Roberto Santana Jose A. Lozano SILM AAML 33 11 0 05 Jul 2021
Promises and Pitfalls of Black-Box Concept Learning Models Anita Mahinpei Justin Clark Isaac Lage Finale Doshi-Velez Weiwei Pan 31 91 0 24 Jun 2021
Interpretable Face Manipulation Detection via Feature Whitening Yingying Hua Daichi Zhang Pengju Wang Shiming Ge AAML FAtt CVBM 11 2 0 21 Jun 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lió Marco Gori S. Melacci FAtt XAI 23 78 0 12 Jun 2021
Memory Wrap: a Data-Efficient and Interpretable Extension to Image Classification Models B. La Rosa Roberto Capobianco Daniele Nardi VLM 17 9 0 01 Jun 2021
The Definitions of Interpretability and Learning of Interpretable Models Weishen Pan Changshui Zhang FaML XAI 11 3 0 29 May 2021
Explainable Machine Learning with Prior Knowledge: An Overview Katharina Beckh Sebastian Müller Matthias Jakobs Vanessa Toborek Hanxiao Tan Raphael Fischer Pascal Welke Sebastian Houben Laura von Rueden XAI 22 28 0 21 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 26 184 0 15 May 2021
Cause and Effect: Hierarchical Concept-based Explanation of Neural Networks Mohammad Nokhbeh Zaeem Majid Komeili CML 10 9 0 14 May 2021
Ethical Implementation of Artificial Intelligence to Select Embryos in In Vitro Fertilization M. Afnan Cynthia Rudin Vincent Conitzer J. Savulescu Abhishek Mishra Yanhe Liu M. Afnan SyDa 25 17 0 30 Apr 2021
Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches Dmitry Kazhdan B. Dimanov Helena Andrés-Terré M. Jamnik Pietro Lió Adrian Weller CoGe DRL 12 22 0 14 Apr 2021
Dataset Summarization by K Principal Concepts Niv Cohen Yedid Hoshen 11 1 0 08 Apr 2021
Deep Interpretable Models of Theory of Mind Ini Oguntola Dana Hughes Katia P. Sycara HAI 25 23 0 07 Apr 2021
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography A. Barnett F. Schwartz Chaofan Tao Chaofan Chen Yinhao Ren J. Lo Cynthia Rudin 31 133 0 23 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 59 653 0 20 Mar 2021
Deep Learning Based Decision Support for Medicine -- A Case Study on Skin Cancer Diagnosis Adriano Lucieri Andreas Dengel Sheraz Ahmed 9 7 0 02 Mar 2021
Achieving Explainability for Plant Disease Classification with Disentangled Variational Autoencoders Harshana Habaragamuwa Y. Oishi Kenichi Tanaka 14 7 0 05 Feb 2021
Progressive Interpretation Synthesis: Interpreting Task Solving by Quantifying Previously Used and Unused Information Zhengqi He Taro Toyoizumi 15 1 0 08 Jan 2021
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski 19 111 0 29 Nov 2020
Debiasing Convolutional Neural Networks via Meta Orthogonalization Kurtis Evan David Qiang Liu Ruth C. Fong FaML 17 3 0 15 Nov 2020
MACE: Model Agnostic Concept Extractor for Explaining Image Classification Networks Ashish Kumar Karan Sehgal Prerna Garg V. Kamakshi N. C. Krishnan FAtt 6 9 0 03 Nov 2020
A Framework to Learn with Interpretation Jayneel Parekh Pavlo Mozharovskyi Florence dÁlché-Buc AI4CE FAtt 17 30 0 19 Oct 2020
Normalization Techniques in Training DNNs: Methodology, Analysis and Application Lei Huang Jie Qin Yi Zhou Fan Zhu Li Liu Ling Shao AI4CE 10 254 0 27 Sep 2020
Error Autocorrelation Objective Function for Improved System Modeling Anand Ramakrishnan Warren B.Jackson Kent Evans DRL 16 0 0 08 Aug 2020
Concept Bottleneck Models Pang Wei Koh Thao Nguyen Y. S. Tang Stephen Mussmann Emma Pierson Been Kim Percy Liang 17 776 0 09 Jul 2020
Corpus-level and Concept-based Explanations for Interpretable Document Classification Tian Shi Xuchao Zhang Ping Wang Chandan K. Reddy FAtt 21 8 0 24 Apr 2020
Architecture Disentanglement for Deep Neural Networks Jie Hu Liujuan Cao QiXiang Ye Tong Tong Shengchuan Zhang Ke Li Feiyue Huang Rongrong Ji Ling Shao AAML 31 16 0 30 Mar 2020
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan Ö. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 122 297 0 17 Oct 2019