Explaining Explanations: An Overview of Interpretability of Machine Learning

31 May 2018

Papers citing "Explaining Explanations: An Overview of Interpretability of Machine Learning"

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Title
Focus! Rating XAI Methods and Finding Biases Anna Arias-Duart Ferran Parés Dario Garcia-Gasulla Víctor Giménez-Ábalos 13 32 0 28 Sep 2021
An Objective Metric for Explainable AI: How and Why to Estimate the Degree of Explainability Francesco Sovrano F. Vitali 29 30 0 11 Sep 2021
Discretized Integrated Gradients for Explaining Language Models Soumya Sanyal Xiang Ren FAtt 9 53 0 31 Aug 2021
Lizard: A Large-Scale Dataset for Colonic Nuclear Instance Segmentation and Classification S. Graham Mostafa Jahanifar A. Azam M. Nimir Yee Wah Tsang ... S. Raza H. Eldaly K. Gopalakrishnan David R. J. Snead Nasir M. Rajpoot 28 123 0 25 Aug 2021
Underreporting of errors in NLG output, and what to do about it Emiel van Miltenburg Miruna Clinciu Ondrej Dusek Dimitra Gkatzia Stephanie Inglis ... Saad Mahamood Emma Manning S. Schoch Craig Thomson Luou Wen 25 38 0 02 Aug 2021
Knowledge-intensive Language Understanding for Explainable AI A. Sheth Manas Gaur Kaushik Roy Keyur Faldu 19 48 0 02 Aug 2021
Trusting RoBERTa over BERT: Insights from CheckListing the Natural Language Inference Task Ishan Tarunesh Somak Aditya Monojit Choudhury 13 17 0 15 Jul 2021
A Review on Explainability in Multimodal Deep Neural Nets Gargi Joshi Rahee Walambe K. Kotecha 21 137 0 17 May 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 21 184 0 15 May 2021
From Distributed Machine Learning to Federated Learning: A Survey Ji Liu Jizhou Huang Yang Zhou Xuhong Li Shilei Ji Haoyi Xiong Dejing Dou FedML OOD 44 243 0 29 Apr 2021
Exploiting Explanations for Model Inversion Attacks Xu Zhao Wencan Zhang Xiao Xiao Brian Y. Lim MIACV 21 82 0 26 Apr 2021
Translational NLP: A New Paradigm and General Principles for Natural Language Processing Research Denis R. Newman-Griffis J. Lehman Carolyn Rose H. Hochheiser 24 20 0 16 Apr 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics Valerie Chen Jeffrey Li Joon Sik Kim Gregory Plumb Ameet Talwalkar 24 29 0 10 Mar 2021
CausalX: Causal Explanations and Block Multilinear Factor Analysis M. Alex O. Vasilescu Eric Kim Xiao-Song Zeng CML 15 10 0 25 Feb 2021
Probing Multimodal Embeddings for Linguistic Properties: the Visual-Semantic Case Adam Dahlgren Lindström Suna Bensch Johanna Björklund F. Drewes 16 20 0 22 Feb 2021
Intuitively Assessing ML Model Reliability through Example-Based Explanations and Editing Model Inputs Harini Suresh Kathleen M. Lewis John Guttag Arvind Satyanarayan FAtt 32 25 0 17 Feb 2021
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research Markus Langer Daniel Oster Timo Speith Holger Hermanns Lena Kästner Eva Schmidt Andreas Sesing Kevin Baum XAI 53 415 0 15 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
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
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
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning Iro Laina Ruth C. Fong Andrea Vedaldi OCL 20 13 0 27 Oct 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
Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision Max Glockner Ivan Habernal Iryna Gurevych LRM 14 25 0 07 Oct 2020
Explaining Deep Neural Networks Oana-Maria Camburu XAI FAtt 20 26 0 04 Oct 2020
Pocket Diagnosis: Secure Federated Learning against Poisoning Attack in the Cloud Zhuo Ma Jianfeng Ma Yinbin Miao Ximeng Liu K. Choo R. Deng FedML 10 32 0 23 Sep 2020
Captum: A unified and generic model interpretability library for PyTorch Narine Kokhlikyan Vivek Miglani Miguel Martin Edward Wang B. Alsallakh ... Alexander Melnikov Natalia Kliushkina Carlos Araya Siqi Yan Orion Reblitz-Richardson FAtt 17 821 0 16 Sep 2020
A Systematic Literature Review on the Use of Deep Learning in Software Engineering Research Cody Watson Nathan Cooper David Nader-Palacio Kevin Moran Denys Poshyvanyk 26 111 0 14 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
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
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 25 625 0 01 Jul 2020
Explainable CNN-attention Networks (C-Attention Network) for Automated Detection of Alzheimer's Disease Ning Wang Mingxuan Chen K. P. Subbalakshmi 14 22 0 25 Jun 2020
To Explain or Not to Explain: A Study on the Necessity of Explanations for Autonomous Vehicles Yuan-Chung Shen Shanduojiao Jiang Yanlin Chen Katie Driggs Campbell 29 41 0 21 Jun 2020
Evaluating and Aggregating Feature-based Model Explanations Umang Bhatt Adrian Weller J. M. F. Moura XAI 28 218 0 01 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
Complaint-driven Training Data Debugging for Query 2.0 Weiyuan Wu Lampros Flokas Eugene Wu Jiannan Wang 19 43 0 12 Apr 2020
GAMI-Net: An Explainable Neural Network based on Generalized Additive Models with Structured Interactions Zebin Yang Aijun Zhang Agus Sudjianto FAtt 12 126 0 16 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and Evaluation Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 18 212 0 09 Mar 2020
TIME: A Transparent, Interpretable, Model-Adaptive and Explainable Neural Network for Dynamic Physical Processes Gurpreet Singh Soumyajit Gupta Matt Lease Clint Dawson AI4TS AI4CE 11 2 0 05 Mar 2020
Interpretability of machine learning based prediction models in healthcare Gregor Stiglic Primož Kocbek Nino Fijačko Marinka Zitnik K. Verbert Leona Cilar AI4CE 29 372 0 20 Feb 2020
Convex Density Constraints for Computing Plausible Counterfactual Explanations André Artelt Barbara Hammer 19 47 0 12 Feb 2020
Interpretability of Blackbox Machine Learning Models through Dataview Extraction and Shadow Model creation Rupam Patir Shubham Singhal C. Anantaram Vikram Goyal 9 0 0 02 Feb 2020
Making deep neural networks right for the right scientific reasons by interacting with their explanations P. Schramowski Wolfgang Stammer Stefano Teso Anna Brugger Xiaoting Shao Hans-Georg Luigs Anne-Katrin Mahlein Kristian Kersting 13 207 0 15 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 30 300 0 08 Jan 2020
Questioning the AI: Informing Design Practices for Explainable AI User Experiences Q. V. Liao D. Gruen Sarah Miller 37 701 0 08 Jan 2020
Artificial Intelligence for Social Good: A Survey Zheyuan Ryan Shi Claire Wang Fei Fang AI4TS 24 81 0 07 Jan 2020
Natural Language Generation Challenges for Explainable AI Ehud Reiter 11 39 0 20 Nov 2019
An explanation method for Siamese neural networks Lev V. Utkin M. Kovalev E. Kasimov 8 14 0 18 Nov 2019
On the computation of counterfactual explanations -- A survey André Artelt Barbara Hammer LRM 22 50 0 15 Nov 2019