Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey

16 June 2020

Papers citing "Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey"

37 / 87 papers shown

Title
A Meta-Analysis of the Utility of Explainable Artificial Intelligence in Human-AI Decision-Making Max Schemmer Patrick Hemmer Maximilian Nitsche Niklas Kühl Michael Vossing 19 55 0 10 May 2022
Perception Visualization: Seeing Through the Eyes of a DNN Loris Giulivi Mark J. Carman Giacomo Boracchi 18 6 0 21 Apr 2022
Using Decision Tree as Local Interpretable Model in Autoencoder-based LIME Niloofar Ranjbar Reza Safabakhsh FAtt 18 5 0 07 Apr 2022
Explainability in reinforcement learning: perspective and position Agneza Krajna Mario Brčič T. Lipić Juraj Dončević 28 27 0 22 Mar 2022
Human-Centric Artificial Intelligence Architecture for Industry 5.0 Applications Jovze M. Rovzanec I. Novalija Patrik Zajec K. Kenda Hooman Tavakoli ... G. Sofianidis Spyros Theodoropoulos Blavz Fortuna Dunja Mladenić John Soldatos 3DV AI4CE 32 119 0 21 Mar 2022
A Survey on Privacy for B5G/6G: New Privacy Challenges, and Research Directions Chamara Sandeepa Bartlomiej Siniarski N. Kourtellis Shen Wang Madhusanka Liyanage 29 21 0 08 Mar 2022
Label-Free Explainability for Unsupervised Models Jonathan Crabbé M. Schaar FAtt MILM 19 22 0 03 Mar 2022
Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods Dominique Mercier Jwalin Bhatt Andreas Dengel Sheraz Ahmed AI4TS 22 11 0 08 Feb 2022
Investigating the fidelity of explainable artificial intelligence methods for applications of convolutional neural networks in geoscience Antonios Mamalakis E. Barnes I. Ebert‐Uphoff 19 73 0 07 Feb 2022
SyntEO: Synthetic Data Set Generation for Earth Observation and Deep Learning -- Demonstrated for Offshore Wind Farm Detection Thorsten Hoeser C. Kuenzer 35 19 0 06 Dec 2021
STEEX: Steering Counterfactual Explanations with Semantics P. Jacob Éloi Zablocki H. Ben-younes Mickaël Chen P. Pérez Matthieu Cord 19 43 0 17 Nov 2021
A Survey on AI Assurance Feras A. Batarseh Laura J. Freeman 29 65 0 15 Nov 2021
Revisiting Methods for Finding Influential Examples Karthikeyan K Anders Søgaard TDI 14 30 0 08 Nov 2021
Explaining Latent Representations with a Corpus of Examples Jonathan Crabbé Zhaozhi Qian F. Imrie M. Schaar FAtt 16 37 0 28 Oct 2021
A Framework for Learning to Request Rich and Contextually Useful Information from Humans Khanh Nguyen Yonatan Bisk Hal Daumé 41 16 0 14 Oct 2021
Explaining Bayesian Neural Networks Kirill Bykov Marina M.-C. Höhne Adelaida Creosteanu Klaus-Robert Muller Frederick Klauschen Shinichi Nakajima Marius Kloft BDL AAML 31 25 0 23 Aug 2021
A Framework and Benchmarking Study for Counterfactual Generating Methods on Tabular Data Raphael Mazzine David Martens 16 33 0 09 Jul 2021
General Board Game Concepts Éric Piette Matthew Stephenson Dennis J. N. J. Soemers C. Browne 16 13 0 02 Jul 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White W. Neiswanger 34 65 0 23 Jun 2021
Entropy-based Logic Explanations of Neural Networks Pietro Barbiero Gabriele Ciravegna Francesco Giannini Pietro Lió Marco Gori S. Melacci FAtt XAI 21 78 0 12 Jun 2021
Evaluating the Correctness of Explainable AI Algorithms for Classification Orcun Yalcin Xiuyi Fan Siyuan Liu XAI FAtt 16 15 0 20 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
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark Dataset Antonios Mamalakis I. Ebert‐Uphoff E. Barnes OOD 25 75 0 18 Mar 2021
Explanations in Autonomous Driving: A Survey Daniel Omeiza Helena Webb Marina Jirotka Lars Kunze 11 214 0 09 Mar 2021
Counterfactuals and Causability in Explainable Artificial Intelligence: Theory, Algorithms, and Applications Yu-Liang Chou Catarina Moreira P. Bruza Chun Ouyang Joaquim A. Jorge CML 44 176 0 07 Mar 2021
Ensembles of Random SHAPs Lev V. Utkin A. Konstantinov FAtt 16 20 0 04 Mar 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
Probing Model Signal-Awareness via Prediction-Preserving Input Minimization Sahil Suneja Yunhui Zheng Yufan Zhuang Jim Laredo Alessandro Morari AAML 24 32 0 25 Nov 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 33 62 0 11 Sep 2020
Learning from Few Samples: A Survey Nihar Bendre Hugo Terashima-Marín Peyman Najafirad VLM BDL 24 54 0 30 Jul 2020
General Pitfalls of Model-Agnostic Interpretation Methods for Machine Learning Models Christoph Molnar Gunnar Konig J. Herbinger Timo Freiesleben Susanne Dandl Christian A. Scholbeck Giuseppe Casalicchio Moritz Grosse-Wentrup B. Bischl FAtt AI4CE 13 135 0 08 Jul 2020
Counterfactual explanation of machine learning survival models M. Kovalev Lev V. Utkin CML OffRL 24 19 0 26 Jun 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
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 251 3,683 0 28 Feb 2017
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 261 3,109 0 04 Nov 2016
Adversarial examples in the physical world Alexey Kurakin Ian Goodfellow Samy Bengio SILM AAML 287 5,835 0 08 Jul 2016