v1v2 (latest)

Interpretation of Neural Networks is Fragile

AAAI Conference on Artificial Intelligence (AAAI), 2017

29 October 2017

Papers citing "Interpretation of Neural Networks is Fragile"

50 / 489 papers shown

Title
Explaining Neural Networks by Decoding Layer ActivationsInternational Symposium on Intelligent Data Analysis (IDA), 2020 Johannes Schneider Michalis Vlachos AI4CE 198 16 0 27 May 2020
NILE : Natural Language Inference with Faithful Natural Language ExplanationsAnnual Meeting of the Association for Computational Linguistics (ACL), 2020 Sawan Kumar Partha P. Talukdar XAI LRM 259 169 0 25 May 2020
Multi-Task Learning in Histo-pathology for Widely Generalizable Model Jevgenij Gamper Navid Alemi Koohbanani Nasir M. Rajpoot 140 7 0 09 May 2020
Towards Frequency-Based Explanation for Robust CNN Zifan Wang Yilin Yang Ankit Shrivastava Varun Rawal Zihao Ding AAML FAtt 151 53 0 06 May 2020
Evaluating and Aggregating Feature-based Model ExplanationsInternational Joint Conference on Artificial Intelligence (IJCAI), 2020 Umang Bhatt Adrian Weller J. M. F. Moura XAI 301 268 0 01 May 2020
Hide-and-Seek: A Template for Explainable AI Thanos Tagaris A. Stafylopatis 100 6 0 30 Apr 2020
Corpus-level and Concept-based Explanations for Interpretable Document ClassificationACM Transactions on Knowledge Discovery from Data (TKDD), 2020 Tian Shi Xuchao Zhang Ping Wang Chandan K. Reddy FAtt 218 10 0 24 Apr 2020
Adversarial Attacks and Defenses: An Interpretation Perspective Ninghao Liu Mengnan Du Ruocheng Guo Huan Liu Helen Zhou AAML 158 8 0 23 Apr 2020
Live Trojan Attacks on Deep Neural Networks Robby Costales Chengzhi Mao R. Norwitz Bryan Kim Junfeng Yang AAML 262 24 0 22 Apr 2020
Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?Annual Meeting of the Association for Computational Linguistics (ACL), 2020 Alon Jacovi Yoav Goldberg XAI 486 682 0 07 Apr 2020
PanNuke Dataset Extension, Insights and Baselines Jevgenij Gamper Navid Alemi Koohbanani Ksenija Benes S. Graham Mostafa Jahanifar S. Khurram A. Azam K. Hewitt Nasir M. Rajpoot 679 214 0 24 Mar 2020
Robust Out-of-distribution Detection for Neural Networks Jiefeng Chen Shouqing Yang Xi Wu Yingyu Liang S. Jha OODD 484 98 0 21 Mar 2020
Heat and Blur: An Effective and Fast Defense Against Adversarial Examples Haya Brama Tal Grinshpoun AAML 165 8 0 17 Mar 2020
Model Agnostic Multilevel ExplanationsNeural Information Processing Systems (NeurIPS), 2020 Karthikeyan N. Ramamurthy B. Vinzamuri Yunfeng Zhang Amit Dhurandhar 174 45 0 12 Mar 2020
Causal Interpretability for Machine Learning -- Problems, Methods and EvaluationSIGKDD Explorations (SIGKDD Explor.), 2020 Raha Moraffah Mansooreh Karami Ruocheng Guo A. Raglin Huan Liu CML ELM XAI 236 240 0 09 Mar 2020
SAM: The Sensitivity of Attribution Methods to Hyperparameters Naman Bansal Chirag Agarwal Anh Nguyen FAtt 137 0 0 04 Mar 2020
A Distributional Framework for Data ValuationInternational Conference on Machine Learning (ICML), 2020 Amirata Ghorbani Michael P. Kim James Zou TDI 120 145 0 27 Feb 2020
Neuron Shapley: Discovering the Responsible NeuronsNeural Information Processing Systems (NeurIPS), 2020 Amirata Ghorbani James Zou FAtt TDI 222 134 0 23 Feb 2020
Bayes-TrEx: a Bayesian Sampling Approach to Model Transparency by Example Serena Booth Yilun Zhou Ankit J. Shah J. Shah BDL 276 2 0 19 Feb 2020
Interpreting Interpretations: Organizing Attribution Methods by Criteria Zifan Wang Piotr (Peter) Mardziel Anupam Datta Matt Fredrikson XAI FAtt 151 18 0 19 Feb 2020
Explaining Explanations: Axiomatic Feature Interactions for Deep NetworksJournal of machine learning research (JMLR), 2020 Joseph D. Janizek Pascal Sturmfels Su-In Lee FAtt 638 167 0 10 Feb 2020
DANCE: Enhancing saliency maps using decoysInternational Conference on Machine Learning (ICML), 2020 Y. Lu Wenbo Guo Masashi Sugiyama William Stafford Noble AAML 228 14 0 03 Feb 2020
Explain Your Move: Understanding Agent Actions Using Specific and Relevant Feature AttributionInternational Conference on Learning Representations (ICLR), 2019 Nikaash Puri Sukriti Verma Piyush B. Gupta Dhruv Kayastha Shripad Deshmukh Balaji Krishnamurthy Sameer Singh FAtt AAML 269 94 0 23 Dec 2019
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness Adam Noack Isaac Ahern Dejing Dou Boyang Albert Li OOD AAML 417 10 0 07 Dec 2019
Attributional Robustness Training using Input-Gradient Spatial Alignment M. Singh Nupur Kumari Puneet Mangla Abhishek Sinha V. Balasubramanian Balaji Krishnamurthy OOD 334 10 0 29 Nov 2019
Towards a Unified Evaluation of Explanation Methods without Ground Truth Hao Zhang Jiayi Chen Haotian Xue Quanshi Zhang XAI 178 9 0 20 Nov 2019
Enhancing the Extraction of Interpretable Information for Ischemic Stroke Imaging from Deep Neural Networks Erico Tjoa Heng Guo Yuhao Lu Cuntai Guan FAtt 123 5 0 19 Nov 2019
"How do I fool you?": Manipulating User Trust via Misleading Black Box ExplanationsAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2019 Himabindu Lakkaraju Osbert Bastani 188 273 0 15 Nov 2019
Patch augmentation: Towards efficient decision boundaries for neural networks Marcus D. Bloice P. Roth Andreas Holzinger AAML 89 2 0 08 Nov 2019
Fooling LIME and SHAP: Adversarial Attacks on Post hoc Explanation MethodsAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2019 Dylan Slack Sophie Hilgard Emily Jia Sameer Singh Himabindu Lakkaraju FAtt AAML MLAU 461 939 0 06 Nov 2019
Explanation by Progressive ExaggerationInternational Conference on Learning Representations (ICLR), 2019 Sumedha Singla Brian Pollack Junxiang Chen Kayhan Batmanghelich FAtt MedIm 370 111 0 01 Nov 2019
CXPlain: Causal Explanations for Model Interpretation under UncertaintyNeural Information Processing Systems (NeurIPS), 2019 Patrick Schwab W. Karlen FAtt CML 292 229 0 27 Oct 2019
Who's responsible? Jointly quantifying the contribution of the learning algorithm and training dataAAAI/ACM Conference on AI, Ethics, and Society (AIES), 2019 G. Yona Amirata Ghorbani James Zou TDI 126 15 0 09 Oct 2019
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks Mehdi Neshat Zifan Wang Bradley Alexander Fan Yang Zijian Zhang Sirui Ding Markus Wagner Helen Zhou FAtt 378 1,283 0 03 Oct 2019
Interrogating the Explanatory Power of Attention in Neural Machine TranslationConference on Empirical Methods in Natural Language Processing (EMNLP), 2019 Pooya Moradi Nishant Kambhatla Anoop Sarkar 224 17 0 30 Sep 2019
Saliency Methods for Explaining Adversarial Attacks Jindong Gu Volker Tresp FAtt AAML 181 33 0 22 Aug 2019
A Tour of Convolutional Networks Guided by Linear InterpretersIEEE International Conference on Computer Vision (ICCV), 2019 Pablo Navarrete Michelini Hanwen Liu Yunhua Lu Xingqun Jiang HAI FAtt 149 8 0 14 Aug 2019
How to Manipulate CNNs to Make Them Lie: the GradCAM Case T. Viering Ziqi Wang Marco Loog E. Eisemann AAML FAtt 114 30 0 25 Jul 2019
Benchmarking Attribution Methods with Relative Feature Importance Mengjiao Yang Been Kim FAtt XAI 157 152 0 23 Jul 2019
A Survey on Explainable Artificial Intelligence (XAI): Towards Medical XAIIEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2019 Erico Tjoa Cuntai Guan XAI 542 1,739 0 17 Jul 2019
Evaluating Explanation Without Ground Truth in Interpretable Machine Learning Fan Yang Mengnan Du Helen Zhou XAI ELM 169 76 0 16 Jul 2019
A study on the Interpretability of Neural Retrieval Models using DeepSHAPAnnual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), 2019 Zeon Trevor Fernando Jaspreet Singh Avishek Anand FAtt AAML 98 76 0 15 Jul 2019
Towards Robust, Locally Linear Deep NetworksInternational Conference on Learning Representations (ICLR), 2019 Guang-He Lee David Alvarez-Melis Tommi Jaakkola ODL 186 48 0 07 Jul 2019
Explanations can be manipulated and geometry is to blameNeural Information Processing Systems (NeurIPS), 2019 Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 308 362 0 19 Jun 2019
Is Attention Interpretable?Annual Meeting of the Association for Computational Linguistics (ACL), 2019 Sofia Serrano Noah A. Smith 373 744 0 09 Jun 2019
ML-LOO: Detecting Adversarial Examples with Feature AttributionAAAI Conference on Artificial Intelligence (AAAI), 2019 Puyudi Yang Jianbo Chen Cho-Jui Hsieh Jane-ling Wang Sai Li AAML 157 110 0 08 Jun 2019
Relaxed Parameter Sharing: Effectively Modeling Time-Varying Relationships in Clinical Time-SeriesMachine Learning in Health Care (MLHC), 2019 Jeeheh Oh Jiaxuan Wang Shengpu Tang Michael Sjoding Jenna Wiens OOD 121 12 0 07 Jun 2019
Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network RobustnessNature Machine Intelligence (NMI), 2019 Walt Woods Jack H Chen C. Teuscher AAML 213 49 0 07 Jun 2019
XRAI: Better Attributions Through RegionsIEEE International Conference on Computer Vision (ICCV), 2019 A. Kapishnikov Tolga Bolukbasi Fernanda Viégas Michael Terry FAtt XAI 188 242 0 06 Jun 2019
Boosting Operational DNN Testing Efficiency through Conditioning Zenan Li Xiaoxing Ma Chang Xu Chun Cao Jingwei Xu Jian Lu 172 110 0 06 Jun 2019