SmoothGrad: removing noise by adding noise

12 June 2017

Papers citing "SmoothGrad: removing noise by adding noise"

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Title
Best of both worlds: local and global explanations with human-understandable concepts Jessica Schrouff Sebastien Baur Shaobo Hou Diana Mincu Eric Loreaux Ralph Blanes James Wexler Alan Karthikesalingam Been Kim FAtt 34 28 0 16 Jun 2021
SEEN: Sharpening Explanations for Graph Neural Networks using Explanations from Neighborhoods Hyeoncheol Cho Youngrock Oh Eunjoo Jeon FAtt 19 0 0 16 Jun 2021
Keep CALM and Improve Visual Feature Attribution Jae Myung Kim Junsuk Choe Zeynep Akata Seong Joon Oh FAtt 350 20 0 15 Jun 2021
Taxonomy of Machine Learning Safety: A Survey and Primer Sina Mohseni Haotao Wang Zhiding Yu Chaowei Xiao Zhangyang Wang J. Yadawa 31 31 0 09 Jun 2021
On the Lack of Robust Interpretability of Neural Text Classifiers Muhammad Bilal Zafar Michele Donini Dylan Slack Cédric Archambeau Sanjiv Ranjan Das K. Kenthapadi AAML 16 21 0 08 Jun 2021
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of Attention T. Gomez Suiyi Ling Thomas Fréour Harold Mouchère 34 5 0 04 Jun 2021
Contrastive ACE: Domain Generalization Through Alignment of Causal Mechanisms Yunqi Wang Furui Liu Zhitang Chen Qing Lian Guangyong Chen Jianye Hao Yik-Chung Wu OOD CML 33 35 0 02 Jun 2021
The Out-of-Distribution Problem in Explainability and Search Methods for Feature Importance Explanations Peter Hase Harry Xie Joey Tianyi Zhou OODD LRM FAtt 29 91 0 01 Jun 2021
COV-ECGNET: COVID-19 detection using ECG trace images with deep convolutional neural network Tawsifur Rahman A. Akinbi M. Chowdhury Tarik A. Rashid Abdulkadir cSengur Amith Khandakar K. R. Islam A. M. Ismael 24 77 0 01 Jun 2021
Distribution Matching for Rationalization Yongfeng Huang Yujun Chen Yulun Du Zhilin Yang OOD 34 16 0 01 Jun 2021
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals Asma Ghandeharioun Been Kim Chun-Liang Li Brendan Jou B. Eoff Rosalind W. Picard AAML 35 53 0 31 May 2021
The effectiveness of feature attribution methods and its correlation with automatic evaluation scores Giang Nguyen Daeyoung Kim Anh Totti Nguyen FAtt 21 86 0 31 May 2021
Bounded logit attention: Learning to explain image classifiers Thomas Baumhauer D. Slijepcevic Matthias Zeppelzauer FAtt 19 2 0 31 May 2021
Attention Flows are Shapley Value Explanations Kawin Ethayarajh Dan Jurafsky FAtt TDI 32 34 0 31 May 2021
EDDA: Explanation-driven Data Augmentation to Improve Explanation Faithfulness Ruiwen Li Zhibo Zhang Jiani Li C. Trabelsi Scott Sanner Jongseong Jang Yeonjeong Jeong Dongsub Shim AAML 16 1 0 29 May 2021
A General Taylor Framework for Unifying and Revisiting Attribution Methods Huiqi Deng Na Zou Mengnan Du Weifu Chen Guo-Can Feng Xia Hu TDI FAtt 44 2 0 28 May 2021
Balancing Robustness and Sensitivity using Feature Contrastive Learning Seungyeon Kim Daniel Glasner Srikumar Ramalingam Cho-Jui Hsieh Kishore Papineni Sanjiv Kumar 25 1 0 19 May 2021
How to Explain Neural Networks: an Approximation Perspective Hangcheng Dong Bingguo Liu Fengdong Chen Dong Ye Guodong Liu FAtt 20 1 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 34 184 0 15 May 2021
Cause and Effect: Hierarchical Concept-based Explanation of Neural Networks Mohammad Nokhbeh Zaeem Majid Komeili CML 15 9 0 14 May 2021
Biometrics: Trust, but Verify Anil K. Jain Debayan Deb Joshua J. Engelsma FaML 28 80 0 14 May 2021
Sanity Simulations for Saliency Methods Joon Sik Kim Gregory Plumb Ameet Talwalkar FAtt 43 17 0 13 May 2021
What's wrong with this video? Comparing Explainers for Deepfake Detection Samuele Pino Mark J. Carman Paolo Bestagini AAML 20 7 0 12 May 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks Eric Wong Shibani Santurkar A. Madry FAtt 22 88 0 11 May 2021
Improving Molecular Graph Neural Network Explainability with Orthonormalization and Induced Sparsity Ryan Henderson Djork-Arné Clevert F. Montanari 33 26 0 11 May 2021
Do Concept Bottleneck Models Learn as Intended? Andrei Margeloiu Matthew Ashman Umang Bhatt Yanzhi Chen M. Jamnik Adrian Weller SLR 25 92 0 10 May 2021
Partially Interpretable Estimators (PIE): Black-Box-Refined Interpretable Machine Learning Tong Wang Jingyi Yang Yunyi Li Boxiang Wang FAtt 20 5 0 06 May 2021
Where and When: Space-Time Attention for Audio-Visual Explanations Yanbei Chen Thomas Hummel A. Sophia Koepke Zeynep Akata 14 3 0 04 May 2021
Canonical Saliency Maps: Decoding Deep Face Models Thrupthi Ann S. M. I. C. V. Balasubramanian M. Jawahar CVBM 24 8 0 04 May 2021
LFI-CAM: Learning Feature Importance for Better Visual Explanation Kwang Hee Lee Chaewon Park J. Oh Nojun Kwak FAtt 32 27 0 03 May 2021
Explanation-Based Human Debugging of NLP Models: A Survey Piyawat Lertvittayakumjorn Francesca Toni LRM 42 79 0 30 Apr 2021
Interpretable Semantic Photo Geolocation Jonas Theiner Eric Müller-Budack Ralph Ewerth 26 30 0 30 Apr 2021
Inspect, Understand, Overcome: A Survey of Practical Methods for AI Safety Sebastian Houben Stephanie Abrecht Maram Akila Andreas Bär Felix Brockherde ... Serin Varghese Michael Weber Sebastian J. Wirkert Tim Wirtz Matthias Woehrle AAML 13 58 0 29 Apr 2021
Do Feature Attribution Methods Correctly Attribute Features? Yilun Zhou Serena Booth Marco Tulio Ribeiro J. Shah FAtt XAI 38 132 0 27 Apr 2021
Instance-wise Causal Feature Selection for Model Interpretation Pranoy Panda Sai Srinivas Kancheti V. Balasubramanian CML 50 16 0 26 Apr 2021
Exploiting Explanations for Model Inversion Attacks Xu Zhao Wencan Zhang Xiao Xiao Brian Y. Lim MIACV 34 82 0 26 Apr 2021
Towards Rigorous Interpretations: a Formalisation of Feature Attribution Darius Afchar Romain Hennequin Vincent Guigue FAtt 33 20 0 26 Apr 2021
Semiotic Aggregation in Deep Learning Bogdan Musat Razvan Andonie FAtt 25 6 0 22 Apr 2021
Improving Attribution Methods by Learning Submodular Functions Piyushi Manupriya Tarun Ram Menta S. Jagarlapudi V. Balasubramanian TDI 30 6 0 19 Apr 2021
Towards Human-Understandable Visual Explanations:Imperceptible High-frequency Cues Can Better Be Removed Kaili Wang José Oramas Tinne Tuytelaars AAML 27 2 0 16 Apr 2021
Deep Stable Learning for Out-Of-Distribution Generalization Xingxuan Zhang Peng Cui Renzhe Xu Linjun Zhou Yue He Zheyan Shen OOD 38 250 0 16 Apr 2021
Ridge Regression Neural Network for Pediatric Bone Age Assessment Ibrahim Salim A. B. Hamza 19 25 0 15 Apr 2021
Vision Transformer using Low-level Chest X-ray Feature Corpus for COVID-19 Diagnosis and Severity Quantification Sangjoon Park Gwanghyun Kim Y. Oh J. Seo Sang Min Lee Jin Hwan Kim Sungjun Moon Jae-Kwang Lim Jong Chul Ye ViT MedIm 58 97 0 15 Apr 2021
Mutual Information Preserving Back-propagation: Learn to Invert for Faithful Attribution Huiqi Deng Na Zou Weifu Chen Guo-Can Feng Mengnan Du Xia Hu FAtt 39 6 0 14 Apr 2021
Evaluating Saliency Methods for Neural Language Models Shuoyang Ding Philipp Koehn FAtt XAI 23 54 0 12 Apr 2021
A-FMI: Learning Attributions from Deep Networks via Feature Map Importance An Zhang Xiang Wang Chengfang Fang Jie Shi Tat-Seng Chua Zehua Chen FAtt 32 3 0 12 Apr 2021
Enhancing Deep Neural Network Saliency Visualizations with Gradual Extrapolation Tomasz Szandała FAtt 24 4 0 11 Apr 2021
Individual Explanations in Machine Learning Models: A Survey for Practitioners Alfredo Carrillo Luis F. Cantú Alejandro Noriega FaML 24 15 0 09 Apr 2021
Deep Interpretable Models of Theory of Mind Ini Oguntola Dana Hughes Katia Sycara HAI 33 26 0 07 Apr 2021
White Box Methods for Explanations of Convolutional Neural Networks in Image Classification Tasks Meghna P. Ayyar J. Benois-Pineau A. Zemmari FAtt 30 17 0 06 Apr 2021