Model-Agnostic Interpretability of Machine Learning

16 June 2016

Papers citing "Model-Agnostic Interpretability of Machine Learning"

50 / 118 papers shown

Title
Interpreting Embedding Spaces by Conceptualization Adi Simhi Shaul Markovitch 29 5 0 22 Aug 2022
Data Science and Machine Learning in Education G. Benelli Thomas Y. Chen Javier Mauricio Duarte Matthew Feickert Matthew Graham ... K. Terao S. Thais A. Roy J. Vlimant G. Chachamis AI4CE 30 5 0 19 Jul 2022
How Platform-User Power Relations Shape Algorithmic Accountability: A Case Study of Instant Loan Platforms and Financially Stressed Users in India Divya Ramesh Vaishnav Kameswaran Ding-wen Wang Nithya Sambasivan 30 35 0 11 May 2022
The Road to Explainability is Paved with Bias: Measuring the Fairness of Explanations Aparna Balagopalan Haoran Zhang Kimia Hamidieh Thomas Hartvigsen Frank Rudzicz Marzyeh Ghassemi 45 78 0 06 May 2022
Should I Follow AI-based Advice? Measuring Appropriate Reliance in Human-AI Decision-Making Max Schemmer Patrick Hemmer Niklas Kühl Carina Benz G. Satzger 22 56 0 14 Apr 2022
EEG based Emotion Recognition: A Tutorial and Review Xiang Li Yazhou Zhang Prayag Tiwari D. Song Bin Hu Meihong Yang Zhigang Zhao Neeraj Kumar Pekka Marttinen 25 249 0 16 Mar 2022
Counterfactual Explanations for Predictive Business Process Monitoring Tsung-Hao Huang Andreas Metzger Klaus Pohl 32 19 0 24 Feb 2022
The Disagreement Problem in Explainable Machine Learning: A Practitioner's Perspective Satyapriya Krishna Tessa Han Alex Gu Steven Wu S. Jabbari Himabindu Lakkaraju 194 186 0 03 Feb 2022
Interpretable and Generalizable Graph Learning via Stochastic Attention Mechanism Siqi Miao Miaoyuan Liu Pan Li 18 197 0 31 Jan 2022
Measuring Attribution in Natural Language Generation Models Hannah Rashkin Vitaly Nikolaev Matthew Lamm Lora Aroyo Michael Collins Dipanjan Das Slav Petrov Gaurav Singh Tomar Iulia Turc David Reitter 39 174 0 23 Dec 2021
Why Are You Weird? Infusing Interpretability in Isolation Forest for Anomaly Detection Nirmal Sobha Kartha Clément Gautrais Vincent Vercruyssen 19 6 0 13 Dec 2021
Explainable Deep Learning in Healthcare: A Methodological Survey from an Attribution View Di Jin Elena Sergeeva W. Weng Geeticka Chauhan Peter Szolovits OOD 56 55 0 05 Dec 2021
Decorrelated Variable Importance I. Verdinelli Larry A. Wasserman FAtt 17 18 0 21 Nov 2021
Explaining Deep Reinforcement Learning Agents In The Atari Domain through a Surrogate Model Alexander Sieusahai Matthew J. Guzdial 35 13 0 07 Oct 2021
Discriminative Attribution from Counterfactuals N. Eckstein A. S. Bates G. Jefferis Jan Funke FAtt CML 27 1 0 28 Sep 2021
AdjointNet: Constraining machine learning models with physics-based codes S. Karra B. Ahmmed M. Mudunuru AI4CE PINN OOD 24 4 0 08 Sep 2021
Diagnostics-Guided Explanation Generation Pepa Atanasova J. Simonsen Christina Lioma Isabelle Augenstein LRM FAtt 43 6 0 08 Sep 2021
Logic Explained Networks Gabriele Ciravegna Pietro Barbiero Francesco Giannini Marco Gori Pietro Lio Marco Maggini S. Melacci 42 69 0 11 Aug 2021
Levels of explainable artificial intelligence for human-aligned conversational explanations Richard Dazeley Peter Vamplew Cameron Foale Charlotte Young Sunil Aryal F. Cruz 30 90 0 07 Jul 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lio Marco Gori S. Melacci FAtt XAI 30 78 0 12 Jun 2021
Explaining Time Series Predictions with Dynamic Masks Jonathan Crabbé M. Schaar FAtt AI4TS 23 80 0 09 Jun 2021
On Efficiently Explaining Graph-Based Classifiers Xuanxiang Huang Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 41 37 0 02 Jun 2021
To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods E. Amparore Alan Perotti P. Bajardi FAtt 33 68 0 01 Jun 2021
Information-theoretic Evolution of Model Agnostic Global Explanations Sukriti Verma Nikaash Puri Piyush B. Gupta Balaji Krishnamurthy FAtt 29 0 0 14 May 2021
Machine learning approach to dynamic risk modeling of mortality in COVID-19: a UK Biobank study M. Dabbah Angus B. Reed A. Booth A. Yassaee A. Despotovic ... Emily Binning M. Aral D. Plans A. Labrique D. Mohan 14 17 0 19 Apr 2021
Editing Factual Knowledge in Language Models Nicola De Cao Wilker Aziz Ivan Titov KELM 68 478 0 16 Apr 2021
Generative Causal Explanations for Graph Neural Networks Wanyu Lin Hao Lan Baochun Li CML 36 173 0 14 Apr 2021
Individual Explanations in Machine Learning Models: A Case Study on Poverty Estimation Alfredo Carrillo Luis F. Cantú Luis Tejerina Alejandro Noriega 13 2 0 09 Apr 2021
Explainable AI by BAPC -- Before and After correction Parameter Comparison F. Sobieczky Manuela Geiß 16 1 0 12 Mar 2021
Evaluating Robustness of Counterfactual Explanations André Artelt Valerie Vaquet Riza Velioglu Fabian Hinder Johannes Brinkrolf M. Schilling Barbara Hammer 14 46 0 03 Mar 2021
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 33 22 0 14 Feb 2021
Beyond Expertise and Roles: A Framework to Characterize the Stakeholders of Interpretable Machine Learning and their Needs Harini Suresh Steven R. Gomez K. Nam Arvind Satyanarayan 34 126 0 24 Jan 2021
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 59 74 0 18 Jan 2021
Explainable AI for Software Engineering Chakkrit Tantithamthavorn Jirayus Jiarpakdee J. Grundy 29 58 0 03 Dec 2020
TimeSHAP: Explaining Recurrent Models through Sequence Perturbations João Bento Pedro Saleiro André F. Cruz Mário A. T. Figueiredo P. Bizarro FAtt AI4TS 24 88 0 30 Nov 2020
On Explaining Decision Trees Yacine Izza Alexey Ignatiev Sasha Rubin FAtt 24 85 0 21 Oct 2020
Interpreting Graph Neural Networks for NLP With Differentiable Edge Masking M. Schlichtkrull Nicola De Cao Ivan Titov AI4CE 36 214 0 01 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 32 25 0 30 Sep 2020
A Diagnostic Study of Explainability Techniques for Text Classification Pepa Atanasova J. Simonsen Christina Lioma Isabelle Augenstein XAI FAtt 22 220 0 25 Sep 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 29 162 0 11 Aug 2020
Causal Explanations of Image Misclassifications Yan Min Miles K. Bennett CML 16 0 0 28 Jun 2020
Location, location, location: Satellite image-based real-estate appraisal Jan-Peter Kucklick Oliver Müller 28 5 0 04 Jun 2020
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 49 371 0 30 Apr 2020
Sequential Interpretability: Methods, Applications, and Future Direction for Understanding Deep Learning Models in the Context of Sequential Data B. Shickel Parisa Rashidi AI4TS 33 17 0 27 Apr 2020
An Extension of LIME with Improvement of Interpretability and Fidelity Sheng Shi Yangzhou Du Wei Fan FAtt 16 8 0 26 Apr 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 32 213 0 09 Mar 2020
Interpretability of machine learning based prediction models in healthcare Gregor Stiglic Primož Kocbek Nino Fijačko Marinka Zitnik K. Verbert Leona Cilar AI4CE 35 374 0 20 Feb 2020
A Modified Perturbed Sampling Method for Local Interpretable Model-agnostic Explanation Sheng Shi Xinfeng Zhang Wei Fan FAtt 19 28 0 18 Feb 2020
Convex Density Constraints for Computing Plausible Counterfactual Explanations André Artelt Barbara Hammer 19 47 0 12 Feb 2020
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems C. E. Smith Bowen Yu Anjali Srivastava Aaron L Halfaker Loren G. Terveen Haiyi Zhu KELM 21 69 0 14 Jan 2020