"Why Should I Trust You?": Explaining the Predictions of Any Classifier

16 February 2016

Papers citing ""Why Should I Trust You?": Explaining the Predictions of Any Classifier"

50 / 4,309 papers shown

Title
A scalable approach for developing clinical risk prediction applications in different hospitals Hong Sun K. Depraetere Laurent Meesseman J. D. Roo Martijn Vanbiervliet J. Baerdemaeker Herman Muys V. Dossow N. Hulde Ralph Szymanowsky 17 18 0 21 Jan 2021
How can I choose an explainer? An Application-grounded Evaluation of Post-hoc Explanations Sérgio Jesus Catarina Belém Vladimir Balayan João Bento Pedro Saleiro P. Bizarro João Gama 136 119 0 21 Jan 2021
GLocalX -- From Local to Global Explanations of Black Box AI Models Mattia Setzu Riccardo Guidotti A. Monreale Franco Turini D. Pedreschi F. Giannotti 19 116 0 19 Jan 2021
Dissonance Between Human and Machine Understanding Zijian Zhang Jaspreet Singh U. Gadiraju Avishek Anand 59 74 0 18 Jan 2021
Interactive slice visualization for exploring machine learning models C. Hurley Mark O'Connell Katarina Domijan FAtt 21 9 0 18 Jan 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 53 170 0 13 Jan 2021
Explaining the Black-box Smoothly- A Counterfactual Approach Junyu Chen Yong Du Yufan He W. Paul Segars Ye Li MedIm FAtt 70 100 0 11 Jan 2021
Explain and Predict, and then Predict Again Zijian Zhang Koustav Rudra Avishek Anand FAtt 33 51 0 11 Jan 2021
On the Convergence of Tsetlin Machines for the XOR Operator Lei Jiao Xuan Zhang Ole-Christoffer Granmo Kuruge Darshana Abeyrathna 38 31 0 07 Jan 2021
Statistical learning for accurate and interpretable battery lifetime prediction Peter M. Attia Kristen A. Severson J. Witmer 20 51 0 06 Jan 2021
Explainable AI for Robot Failures: Generating Explanations that Improve User Assistance in Fault Recovery Devleena Das Siddhartha Banerjee Sonia Chernova 25 113 0 05 Jan 2021
On the price of explainability for some clustering problems E. Laber Lucas Murtinho 43 26 0 05 Jan 2021
GeCo: Quality Counterfactual Explanations in Real Time Maximilian Schleich Zixuan Geng Yihong Zhang D. Suciu 51 61 0 05 Jan 2021
Local Black-box Adversarial Attacks: A Query Efficient Approach Tao Xiang Hangcheng Liu Shangwei Guo Tianwei Zhang X. Liao AAML MLAU 26 15 0 04 Jan 2021
On Baselines for Local Feature Attributions Johannes Haug Stefan Zurn Peter El-Jiz Gjergji Kasneci FAtt 24 31 0 04 Jan 2021
Outcome-Explorer: A Causality Guided Interactive Visual Interface for Interpretable Algorithmic Decision Making Md. Naimul Hoque Klaus Mueller CML 59 30 0 03 Jan 2021
Polyjuice: Generating Counterfactuals for Explaining, Evaluating, and Improving Models Tongshuang Wu Marco Tulio Ribeiro Jeffrey Heer Daniel S. Weld 60 244 0 01 Jan 2021
Evidence-based Factual Error Correction James Thorne Andreas Vlachos KELM OffRL 29 54 0 31 Dec 2020
iGOS++: Integrated Gradient Optimized Saliency by Bilateral Perturbations Saeed Khorram T. Lawson Fuxin Li AAML FAtt 11 26 0 31 Dec 2020
FastIF: Scalable Influence Functions for Efficient Model Interpretation and Debugging Han Guo Nazneen Rajani Peter Hase Joey Tianyi Zhou Caiming Xiong TDI 46 102 0 31 Dec 2020
Quantitative Evaluations on Saliency Methods: An Experimental Study Xiao-hui Li Yuhan Shi Haoyang Li Wei Bai Yuanwei Song Caleb Chen Cao Lei Chen FAtt XAI 47 18 0 31 Dec 2020
Out of Order: How Important Is The Sequential Order of Words in a Sentence in Natural Language Understanding Tasks? Thang M. Pham Trung Bui Long Mai Anh Totti Nguyen 220 122 0 30 Dec 2020
Playing to distraction: towards a robust training of CNN classifiers through visual explanation techniques David Morales Estefanía Talavera B. Remeseiro 34 6 0 28 Dec 2020
Explaining NLP Models via Minimal Contrastive Editing (MiCE) Alexis Ross Ana Marasović Matthew E. Peters 43 121 0 27 Dec 2020
Inserting Information Bottlenecks for Attribution in Transformers Zhiying Jiang Raphael Tang Ji Xin Jimmy J. Lin 41 6 0 27 Dec 2020
Limitations of Deep Neural Networks: a discussion of G. Marcus' critical appraisal of deep learning Stefanos Tsimenidis 27 12 0 22 Dec 2020
GANterfactual - Counterfactual Explanations for Medical Non-Experts using Generative Adversarial Learning Silvan Mertes Tobias Huber Katharina Weitz Alexander Heimerl Elisabeth André GAN AAML MedIm 39 69 0 22 Dec 2020
Unbox the Blackbox: Predict and Interpret YouTube Viewership Using Deep Learning Jiaheng Xie Xinyu Liu HAI 33 10 0 21 Dec 2020
Explaining Black-box Models for Biomedical Text Classification M. Moradi Matthias Samwald 46 21 0 20 Dec 2020
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 35 63 0 18 Dec 2020
Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease M. Dyrba Moritz Hanzig S. Altenstein Sebastian Bader Tommaso Ballarini ... B. Ertl-Wagner M. Wagner J. Wiltfang F. Jessen S. Teipel FAtt MedIm 55 51 0 18 Dec 2020
HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection Binny Mathew Punyajoy Saha Seid Muhie Yimam Chris Biemann Pawan Goyal Animesh Mukherjee 72 551 0 18 Dec 2020
Semantics and explanation: why counterfactual explanations produce adversarial examples in deep neural networks Kieran Browne Ben Swift AAML GAN 33 29 0 18 Dec 2020
XAI-P-T: A Brief Review of Explainable Artificial Intelligence from Practice to Theory Nazanin Fouladgar Kary Främling XAI 15 4 0 17 Dec 2020
AIST: An Interpretable Attention-based Deep Learning Model for Crime Prediction Yeasir Rayhan T. Hashem 24 22 0 16 Dec 2020
Rule Extraction from Binary Neural Networks with Convolutional Rules for Model Validation Sophie Burkhardt Jannis Brugger Nicolas Wagner Zahra Ahmadi Kristian Kersting Stefan Kramer NAI FAtt 25 8 0 15 Dec 2020
Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision Faeze Brahman Vered Shwartz Rachel Rudinger Yejin Choi LRM 25 42 0 14 Dec 2020
A Software Engineering Perspective on Engineering Machine Learning Systems: State of the Art and Challenges G. Giray 38 121 0 14 Dec 2020
Differentiation of Sliding Rescaled Ranges: New Approach to Encrypted and VPN Traffic Detection R. Nigmatullin Alexander Ivchenko S. Dorokhin 18 4 0 14 Dec 2020
Demystifying Deep Neural Networks Through Interpretation: A Survey Giang Dao Minwoo Lee FaML FAtt 22 1 0 13 Dec 2020
DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation Han Qiu Yi Zeng Shangwei Guo Tianwei Zhang Meikang Qiu B. Thuraisingham AAML 24 191 0 13 Dec 2020
Are We Ready For Learned Cardinality Estimation? Xiaoying Wang Changbo Qu Weiyuan Wu Jiannan Wang Qingqing Zhou 41 113 0 12 Dec 2020
Neurosymbolic AI: The 3rd Wave Artur Garcez Luís C. Lamb NAI 65 293 0 10 Dec 2020
Understanding Learned Reward Functions Eric J. Michaud Adam Gleave Stuart J. Russell XAI OffRL 30 33 0 10 Dec 2020
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 34 18 0 10 Dec 2020
Methodology for Mining, Discovering and Analyzing Semantic Human Mobility Behaviors Clément Moreau T. Devogele Laurent Étienne Verónika Peralta Cyril de Runz 19 1 0 08 Dec 2020
Efficient Estimation of Influence of a Training Instance Sosuke Kobayashi Sho Yokoi Jun Suzuki Kentaro Inui TDI 37 15 0 08 Dec 2020
FuseVis: Interpreting neural networks for image fusion using per-pixel saliency visualization Nishant Kumar Stefan Gumhold AAML MedIm 36 10 0 06 Dec 2020
Deep Learning for Medical Anomaly Detection -- A Survey Tharindu Fernando Harshala Gammulle Simon Denman Sridha Sridharan Clinton Fookes OOD 22 271 0 04 Dec 2020
Interpretability and Explainability: A Machine Learning Zoo Mini-tour Ricards Marcinkevics Julia E. Vogt XAI 33 119 0 03 Dec 2020