Towards A Rigorous Science of Interpretable Machine Learning

28 February 2017

Finale Doshi-Velez

Papers citing "Towards A Rigorous Science of Interpretable Machine Learning"

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Title
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 37 169 0 13 Jan 2021
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging Han Guo Nazneen Rajani Peter Hase Mohit Bansal Caiming Xiong TDI 19 102 0 31 Dec 2020
Fairkit, Fairkit, on the Wall, Who's the Fairest of Them All? Supporting Data Scientists in Training Fair Models Brittany Johnson Jesse Bartola Rico Angell Katherine Keith Sam Witty S. Giguere Yuriy Brun FaML 14 18 0 17 Dec 2020
Developing Future Human-Centered Smart Cities: Critical Analysis of Smart City Security, Interpretability, and Ethical Challenges Kashif Ahmad Majdi Maabreh M. Ghaly Khalil Khan Junaid Qadir Ala I. Al-Fuqaha 19 142 0 14 Dec 2020
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 16 18 0 10 Dec 2020
Neural Prototype Trees for Interpretable Fine-grained Image Recognition Meike Nauta Ron van Bree C. Seifert 66 261 0 03 Dec 2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 16 119 0 03 Dec 2020
Cross-Loss Influence Functions to Explain Deep Network Representations Andrew Silva Rohit Chopra Matthew C. Gombolay TDI 13 15 0 03 Dec 2020
Quantifying Explainers of Graph Neural Networks in Computational Pathology Guillaume Jaume Pushpak Pati Behzad Bozorgtabar Antonio Foncubierta-Rodríguez Florinda Feroce A. Anniciello T. Rau Jean-Philippe Thiran M. Gabrani O. Goksel FAtt 13 76 0 25 Nov 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 11 84 0 12 Nov 2020
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization Judy Borowski Roland S. Zimmermann Judith Schepers Robert Geirhos Thomas S. A. Wallis Matthias Bethge Wieland Brendel FAtt 34 7 0 23 Oct 2020
A Perspective on Machine Learning Methods in Turbulence Modelling Andrea Beck Marius Kurz AI4CE 45 101 0 23 Oct 2020
A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images Pablo Messina Pablo Pino Denis Parra Alvaro Soto Cecilia Besa S. Uribe Marcelo andía C. Tejos Claudia Prieto Daniel Capurro MedIm 28 62 0 20 Oct 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 10 397 0 19 Oct 2020
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making Charvi Rastogi Yunfeng Zhang Dennis L. Wei Kush R. Varshney Amit Dhurandhar Richard J. Tomsett HAI 27 108 0 15 Oct 2020
PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks Minh Nhat Vu My T. Thai BDL 8 327 0 12 Oct 2020
A Series of Unfortunate Counterfactual Events: the Role of Time in Counterfactual Explanations Andrea Ferrario M. Loi 17 5 0 09 Oct 2020
Interpretable Machine Learning for COVID-19: An Empirical Study on Severity Prediction Task Han-Ching Wu Wenjie Ruan Jiangtao Wang Dingchang Zheng Bei Liu ... Xiangfei Chai Jian Chen Kunwei Li Shaolin Li A. Helal 27 25 0 30 Sep 2020
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses Kaivalya Rawal Himabindu Lakkaraju 25 11 0 15 Sep 2020
A Game-Based Approach for Helping Designers Learn Machine Learning Concepts Chelsea M. Myers Jiachi Xie Jichen Zhu 11 4 0 11 Sep 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 27 62 0 11 Sep 2020
Play MNIST For Me! User Studies on the Effects of Post-Hoc, Example-Based Explanations & Error Rates on Debugging a Deep Learning, Black-Box Classifier Courtney Ford Eoin M. Kenny Mark T. Keane 15 6 0 10 Sep 2020
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring Nijat Mehdiyev Peter Fettke AI4TS 25 55 0 04 Sep 2020
Query Understanding via Intent Description Generation Ruqing Zhang Jiafeng Guo Yixing Fan Yanyan Lan Xueqi Cheng 19 17 0 25 Aug 2020
Quantum Language Model with Entanglement Embedding for Question Answering Yiwei Chen Yu Pan D. Dong 20 31 0 23 Aug 2020
Explainable Predictive Process Monitoring Musabir Musabayli F. Maggi Williams Rizzi Josep Carmona Chiara Di Francescomarino 6 60 0 04 Aug 2020
Evaluating the performance of the LIME and Grad-CAM explanation methods on a LEGO multi-label image classification task David Cian J. C. V. Gemert A. Lengyel FAtt 11 22 0 04 Aug 2020
Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance Mattia Carletti M. Terzi Gian Antonio Susto 23 42 0 21 Jul 2020
Sequential Explanations with Mental Model-Based Policies A. Yeung Shalmali Joshi Joseph Jay Williams Frank Rudzicz FAtt LRM 26 15 0 17 Jul 2020
Learning Reasoning Strategies in End-to-End Differentiable Proving Pasquale Minervini Sebastian Riedel Pontus Stenetorp Edward Grefenstette Tim Rocktaschel LRM 37 96 0 13 Jul 2020
Algorithmic Fairness in Education René F. Kizilcec Hansol Lee FaML 35 119 0 10 Jul 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 25 625 0 01 Jul 2020
BERTology Meets Biology: Interpreting Attention in Protein Language Models Jesse Vig Ali Madani L. Varshney Caiming Xiong R. Socher Nazneen Rajani 15 288 0 26 Jun 2020
DeltaGrad: Rapid retraining of machine learning models Yinjun Wu Edgar Dobriban S. Davidson MU 11 194 0 26 Jun 2020
Interpretable Deep Models for Cardiac Resynchronisation Therapy Response Prediction Esther Puyol-Antón C. L. P. Chen J. Clough B. Ruijsink B. Sidhu ... M. Elliott Vishal S. Mehta Daniel Rueckert C. Rinaldi A. King 9 32 0 24 Jun 2020
Fair Performance Metric Elicitation G. Hiranandani Harikrishna Narasimhan Oluwasanmi Koyejo 24 18 0 23 Jun 2020
Does Explainable Artificial Intelligence Improve Human Decision-Making? Y. Alufaisan L. Marusich J. Bakdash Yan Zhou Murat Kantarcioglu XAI 14 93 0 19 Jun 2020
Detecting unusual input to neural networks Jörg Martin Clemens Elster AAML 9 7 0 15 Jun 2020
Getting a CLUE: A Method for Explaining Uncertainty Estimates Javier Antorán Umang Bhatt T. Adel Adrian Weller José Miguel Hernández-Lobato UQCV BDL 32 111 0 11 Jun 2020
How Interpretable and Trustworthy are GAMs? C. Chang S. Tan Benjamin J. Lengerich Anna Goldenberg R. Caruana FAtt 8 76 0 11 Jun 2020
Interpretable Deep Graph Generation with Node-Edge Co-Disentanglement Xiaojie Guo Liang Zhao Zhao Qin Lingfei Wu Amarda Shehu Yanfang Ye CoGe DRL 32 46 0 09 Jun 2020
XGNN: Towards Model-Level Explanations of Graph Neural Networks Haonan Yuan Jiliang Tang Xia Hu Shuiwang Ji 21 389 0 03 Jun 2020
A Performance-Explainability Framework to Benchmark Machine Learning Methods: Application to Multivariate Time Series Classifiers Kevin Fauvel Véronique Masson Elisa Fromont AI4TS 31 17 0 29 May 2020
Local and Global Explanations of Agent Behavior: Integrating Strategy Summaries with Saliency Maps Tobias Huber Katharina Weitz Elisabeth André Ofra Amir FAtt 16 63 0 18 May 2020
Clinical Predictive Models for COVID-19: Systematic Study Patrick Schwab August DuMont Schütte Benedikt Dietz Stefan Bauer OOD ELM 40 35 0 17 May 2020
Explaining Black Box Predictions and Unveiling Data Artifacts through Influence Functions Xiaochuang Han Byron C. Wallace Yulia Tsvetkov MILM FAtt AAML TDI 18 164 0 14 May 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 29 371 0 30 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Xia Hu AAML 24 8 0 23 Apr 2020
CrossCheck: Rapid, Reproducible, and Interpretable Model Evaluation Dustin L. Arendt Zhuanyi Huang Prasha Shrestha Ellyn Ayton M. Glenski Svitlana Volkova 19 8 0 16 Apr 2020
Human Evaluation of Interpretability: The Case of AI-Generated Music Knowledge Haizi Yu Heinrich Taube James A. Evans L. Varshney 6 5 0 15 Apr 2020