Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)

30 November 2017

Justin Gilmer

Papers citing "Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV)"

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VAE-CE: Visual Contrastive Explanation using Disentangled VAEs Y. Poels Vlado Menkovski CoGe DRL 24 3 0 20 Aug 2021
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On the Explanatory Power of Decision Trees Gilles Audemard S. Bellart Louenas Bounia F. Koriche Jean-Marie Lagniez Pierre Marquis FAtt 14 11 0 11 Aug 2021
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Harnessing value from data science in business: ensuring explainability and fairness of solutions Krzysztof Chomiak Michal Miktus 13 0 0 10 Aug 2021
Human-in-the-loop Extraction of Interpretable Concepts in Deep Learning Models Zhenge Zhao Panpan Xu C. Scheidegger Liu Ren 13 38 0 08 Aug 2021
Fairness Properties of Face Recognition and Obfuscation Systems Harrison Rosenberg Brian Tang Kassem Fawaz S. Jha PICV 8 14 0 05 Aug 2021
Reducing Unintended Bias of ML Models on Tabular and Textual Data Guilherme Alves M. Amblard Fabien Bernier Miguel Couceiro A. Napoli FaML 19 15 0 05 Aug 2021
Discovering User-Interpretable Capabilities of Black-Box Planning Agents Pulkit Verma Shashank Rao Marpally Siddharth Srivastava ELM LLMAG 8 20 0 28 Jul 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
Using a Cross-Task Grid of Linear Probes to Interpret CNN Model Predictions On Retinal Images Katy Blumer Subhashini Venugopalan Michael P. Brenner Jon M. Kleinberg 6 0 0 23 Jul 2021
Explainable artificial intelligence (XAI) in deep learning-based medical image analysis Bas H. M. van der Velden Hugo J. Kuijf K. Gilhuijs M. Viergever XAI 29 636 0 22 Jul 2021
Roadmap of Designing Cognitive Metrics for Explainable Artificial Intelligence (XAI) J. H. Hsiao H. Ngai Luyu Qiu Yi Yang Caleb Chen Cao XAI 28 27 0 20 Jul 2021
Shared Interest: Measuring Human-AI Alignment to Identify Recurring Patterns in Model Behavior Angie Boggust Benjamin Hoover Arvindmani Satyanarayan Hendrik Strobelt 27 50 0 20 Jul 2021
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images Weina Jin Xiaoxiao Li Ghassan Hamarneh FAtt 18 16 0 11 Jul 2021
Using Causal Analysis for Conceptual Deep Learning Explanation Sumedha Singla Stephen Wallace Sofia Triantafillou Kayhan Batmanghelich CML 11 14 0 10 Jul 2021
When and How to Fool Explainable Models (and Humans) with Adversarial Examples Jon Vadillo Roberto Santana Jose A. Lozano SILM AAML 36 11 0 05 Jul 2021
Productivity, Portability, Performance: Data-Centric Python Yiheng Wang Yao Zhang Yanzhang Wang Yan Wan Jiao Wang Zhongyuan Wu Yuhao Yang Bowen She 52 94 0 01 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
Towards Fully Interpretable Deep Neural Networks: Are We There Yet? Sandareka Wickramanayake W. Hsu M. Lee FaML AI4CE 13 3 0 24 Jun 2021
Meaningfully Debugging Model Mistakes using Conceptual Counterfactual Explanations Abubakar Abid Mert Yuksekgonul James Y. Zou CML 29 64 0 24 Jun 2021
Not all users are the same: Providing personalized explanations for sequential decision making problems Utkarsh Soni S. Sreedharan Subbarao Kambhampati 12 7 0 23 Jun 2021
Visual Probing: Cognitive Framework for Explaining Self-Supervised Image Representations Witold Oleszkiewicz Dominika Basaj Igor Sieradzki Michal Górszczak Barbara Rychalska K. Lewandowska Tomasz Trzciñski Bartosz Zieliñski SSL 29 3 0 21 Jun 2021
A Game-Theoretic Taxonomy of Visual Concepts in DNNs Xu Cheng Chuntung Chu Yi Zheng Jie Ren Quanshi Zhang 12 21 0 21 Jun 2021
Guided Integrated Gradients: An Adaptive Path Method for Removing Noise A. Kapishnikov Subhashini Venugopalan Besim Avci Benjamin D. Wedin Michael Terry Tolga Bolukbasi 30 90 0 17 Jun 2021
Model-Based Counterfactual Synthesizer for Interpretation Fan Yang Sahan Suresh Alva Jiahao Chen X. Hu 15 30 0 16 Jun 2021
Best of both worlds: local and global explanations with human-understandable concepts Jessica Schrouff Sebastien Baur Shaobo Hou Diana Mincu Eric Loreaux Ralph Blanes James Wexler Alan Karthikesalingam Been Kim FAtt 26 27 0 16 Jun 2021
Keep CALM and Improve Visual Feature Attribution Jae Myung Kim Junsuk Choe Zeynep Akata Seong Joon Oh FAtt 342 20 0 15 Jun 2021
Canonical Face Embeddings David G. McNeely-White Benjamin Sattelberg Nathaniel Blanchard Ross Beveridge CVBM 24 7 0 15 Jun 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lió Marco Gori S. Melacci FAtt XAI 25 78 0 12 Jun 2021
Neural Networks for Partially Linear Quantile Regression Qixian Zhong Jane-ling Wang 13 13 0 11 Jun 2021
Interpreting Expert Annotation Differences in Animal Behavior Megan Tjandrasuwita Jennifer J. Sun Ann Kennedy Swarat Chaudhuri Yisong Yue 14 8 0 11 Jun 2021
Exploiting auto-encoders and segmentation methods for middle-level explanations of image classification systems Andrea Apicella Salvatore Giugliano Francesco Isgrò R. Prevete 6 18 0 09 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 21 31 0 09 Jun 2021
On the Evolution of Neuron Communities in a Deep Learning Architecture Sakib Mostafa Debajyoti Mondal GNN 19 3 0 08 Jun 2021
On the Lack of Robust Interpretability of Neural Text Classifiers Muhammad Bilal Zafar Michele Donini Dylan Slack Cédric Archambeau Sanjiv Ranjan Das K. Kenthapadi AAML 11 21 0 08 Jun 2021
3DB: A Framework for Debugging Computer Vision Models Guillaume Leclerc Hadi Salman Andrew Ilyas Sai H. Vemprala Logan Engstrom ... Pengchuan Zhang Shibani Santurkar Greg Yang Ashish Kapoor A. Madry 40 40 0 07 Jun 2021
Finding and Fixing Spurious Patterns with Explanations Gregory Plumb Marco Tulio Ribeiro Ameet Talwalkar 24 40 0 03 Jun 2021
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals Asma Ghandeharioun Been Kim Chun-Liang Li Brendan Jou B. Eoff Rosalind W. Picard AAML 25 53 0 31 May 2021
The Definitions of Interpretability and Learning of Interpretable Models Weishen Pan Changshui Zhang FaML XAI 11 3 0 29 May 2021
Do not explain without context: addressing the blind spot of model explanations Katarzyna Wo'znica Katarzyna Pkekala Hubert Baniecki Wojciech Kretowicz El.zbieta Sienkiewicz P. Biecek 28 1 0 28 May 2021
Bridging the Gap Between Explainable AI and Uncertainty Quantification to Enhance Trustability Dominik Seuss 17 15 0 25 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
Expressive Explanations of DNNs by Combining Concept Analysis with ILP Johannes Rabold Gesina Schwalbe Ute Schmid 17 22 0 16 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