SmoothGrad: removing noise by adding noise

12 June 2017

Papers citing "SmoothGrad: removing noise by adding noise"

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Title
Discovery of New Multi-Level Features for Domain Generalization via Knowledge Corruption A. Frikha Denis Krompass Volker Tresp OOD 35 1 0 09 Sep 2021
CIM: Class-Irrelevant Mapping for Few-Shot Classification Shuai Shao Lei Xing Yixin Chen Yanjiang Wang Baodi Liu Yicong Zhou 34 2 0 07 Sep 2021
CX-ToM: Counterfactual Explanations with Theory-of-Mind for Enhancing Human Trust in Image Recognition Models Arjun Reddy Akula Keze Wang Changsong Liu Sari Saba-Sadiya Hongjing Lu S. Todorovic J. Chai Song-Chun Zhu 31 47 0 03 Sep 2021
Interactively Providing Explanations for Transformer Language Models Felix Friedrich P. Schramowski Christopher Tauchmann Kristian Kersting LRM 41 6 0 02 Sep 2021
Cross-Model Consensus of Explanations and Beyond for Image Classification Models: An Empirical Study Xuhong Li Haoyi Xiong Siyu Huang Shilei Ji Dejing Dou 30 10 0 02 Sep 2021
Spatio-Temporal Perturbations for Video Attribution Zhenqiang Li Weimin Wang Zuoyue Li Yifei Huang Yoichi Sato 22 6 0 01 Sep 2021
Dead Pixel Test Using Effective Receptive Field Bum Jun Kim Hyeyeon Choi Hyeonah Jang Dong Gu Lee Wonseok Jeong Sang Woo Kim 27 25 0 31 Aug 2021
DuTrust: A Sentiment Analysis Dataset for Trustworthiness Evaluation Lijie Wang Hao Liu Shu-ping Peng Hongxuan Tang Xinyan Xiao Ying-Cong Chen Hua Wu Haifeng Wang 25 5 0 30 Aug 2021
Self-training Improves Pre-training for Few-shot Learning in Task-oriented Dialog Systems Fei Mi Wanhao Zhou Feng Cai Lingjing Kong Minlie Huang Boi Faltings 27 32 0 28 Aug 2021
A Comparison of Deep Saliency Map Generators on Multispectral Data in Object Detection Jens Bayer David Munch Michael Arens 3DPC 35 3 0 26 Aug 2021
Explaining Bayesian Neural Networks Kirill Bykov Marina M.-C. Höhne Adelaida Creosteanu Klaus-Robert Muller Frederick Klauschen Shinichi Nakajima Marius Kloft BDL AAML 36 25 0 23 Aug 2021
Optimising Knee Injury Detection with Spatial Attention and Validating Localisation Ability Niamh Belton I. Welaratne Adil Dahlan Ron Hearne Misgina Tsighe Hagos Aonghus Lawlor Kathleen M. Curran 24 13 0 18 Aug 2021
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better Bojia Zi Shihao Zhao Xingjun Ma Yu-Gang Jiang AAML 22 96 0 18 Aug 2021
Detecting and interpreting faults in vulnerable power grids with machine learning Odin Foldvik Eikeland Inga Setså Holmstrand Sigurd Bakkejord M. Chiesa F. Bianchi 12 13 0 16 Aug 2021
Challenges for cognitive decoding using deep learning methods A. Thomas Christopher Ré R. Poldrack AI4CE 24 6 0 16 Aug 2021
Deep Active Learning for Text Classification with Diverse Interpretations Qiang Liu Yanqiao Zhu Zhaocheng Liu Yufeng Zhang Shu Wu AI4CE 33 14 0 15 Aug 2021
Finding Representative Interpretations on Convolutional Neural Networks P. C. Lam Lingyang Chu Maxim Torgonskiy J. Pei Yong Zhang Lanjun Wang FAtt SSL HAI 27 6 0 13 Aug 2021
Voxel-level Importance Maps for Interpretable Brain Age Estimation Kyriaki-Margarita Bintsi V. Baltatzis A. Hammers Daniel Rueckert 35 12 0 11 Aug 2021
Jujutsu: A Two-stage Defense against Adversarial Patch Attacks on Deep Neural Networks Zitao Chen Pritam Dash Karthik Pattabiraman AAML 32 18 0 11 Aug 2021
Harnessing value from data science in business: ensuring explainability and fairness of solutions Krzysztof Chomiak Michal Miktus 18 0 0 10 Aug 2021
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability Roman Levin Manli Shu Eitan Borgnia Furong Huang Micah Goldblum Tom Goldstein FAtt AAML 28 10 0 03 Aug 2021
Finding Discriminative Filters for Specific Degradations in Blind Super-Resolution Liangbin Xie Xintao Wang Chao Dong Zhongang Qi Ying Shan 14 39 0 02 Aug 2021
Object-aware Contrastive Learning for Debiased Scene Representation Sangwoo Mo H. Kang Kihyuk Sohn Chun-Liang Li Jinwoo Shin SSL OCL 30 49 0 30 Jul 2021
Surrogate Model-Based Explainability Methods for Point Cloud NNs Hanxiao Tan Helena Kotthaus 3DPC 31 26 0 28 Jul 2021
Evaluating the Use of Reconstruction Error for Novelty Localization Patrick Feeney M. C. Hughes 19 3 0 28 Jul 2021
Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks Ian E. Nielsen Dimah Dera Ghulam Rasool N. Bouaynaya R. Ramachandran FAtt 32 79 0 23 Jul 2021
Shared Interest: Measuring Human-AI Alignment to Identify Recurring Patterns in Model Behavior Angie Boggust Benjamin Hoover Arvindmani Satyanarayan Hendrik Strobelt 35 50 0 20 Jul 2021
MEGEX: Data-Free Model Extraction Attack against Gradient-Based Explainable AI T. Miura Satoshi Hasegawa Toshiki Shibahara SILM MIACV 26 37 0 19 Jul 2021
Attribution of Predictive Uncertainties in Classification Models Iker Perez Piotr Skalski Alec E. Barns-Graham Jason Wong David Sutton UQCV 32 6 0 19 Jul 2021
FastSHAP: Real-Time Shapley Value Estimation N. Jethani Mukund Sudarshan Ian Covert Su-In Lee Rajesh Ranganath TDI FAtt 67 127 0 15 Jul 2021
Passive Attention in Artificial Neural Networks Predicts Human Visual Selectivity Thomas A. Langlois H. C. Zhao Erin Grant Ishita Dasgupta Thomas Griffiths Nori Jacoby 52 15 0 14 Jul 2021
One Map Does Not Fit All: Evaluating Saliency Map Explanation on Multi-Modal Medical Images Weina Jin Xiaoxiao Li Ghassan Hamarneh FAtt 26 16 0 11 Jul 2021
Output Randomization: A Novel Defense for both White-box and Black-box Adversarial Models Daniel Park Haidar Khan Azer Khan Alex Gittens B. Yener AAML 21 1 0 08 Jul 2021
A Review of Explainable Artificial Intelligence in Manufacturing G. Sofianidis Jože M. Rožanec Dunja Mladenić D. Kyriazis 25 17 0 05 Jul 2021
Certifiably Robust Interpretation via Renyi Differential Privacy Ao Liu Xiaoyu Chen Sijia Liu Lirong Xia Chuang Gan AAML 27 11 0 04 Jul 2021
Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction Jiahua Rao Shuangjia Zheng Yuedong Yang 21 46 0 01 Jul 2021
Explanation-Guided Diagnosis of Machine Learning Evasion Attacks Abderrahmen Amich Birhanu Eshete AAML 17 10 0 30 Jun 2021
Towards Understanding the Effectiveness of Attention Mechanism Xiang Ye Zihang He Heng Wang Yong Li AAML 39 8 0 29 Jun 2021
Crowdsourcing Evaluation of Saliency-based XAI Methods Xiaotian Lu A. Tolmachev Tatsuya Yamamoto Koh Takeuchi Seiji Okajima T. Takebayashi Koji Maruhashi H. Kashima XAI FAtt 24 14 0 27 Jun 2021
Inverting and Understanding Object Detectors Ang Cao Justin Johnson ObjD 33 3 0 26 Jun 2021
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy Christopher J. Anders David Neumann Wojciech Samek K. Müller Sebastian Lapuschkin 39 64 0 24 Jun 2021
On Locality of Local Explanation Models Sahra Ghalebikesabi Lucile Ter-Minassian Karla Diaz-Ordaz Chris Holmes FedML FAtt 28 39 0 24 Jun 2021
Evaluation of Saliency-based Explainability Method Sam Zabdiel Sunder Samuel V. Kamakshi Namrata Lodhi N. C. Krishnan FAtt XAI 32 12 0 24 Jun 2021
IA-RED $^2$ : Interpretability-Aware Redundancy Reduction for Vision Transformers Bowen Pan Yikang Shen Yi Ding Zhangyang Wang Rogerio Feris A. Oliva VLM ViT 44 156 0 23 Jun 2021
Gradient-Based Interpretability Methods and Binarized Neural Networks Amy Widdicombe S. Julier FAtt 11 0 0 23 Jun 2021
Feature Attributions and Counterfactual Explanations Can Be Manipulated Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 19 6 0 23 Jun 2021
Leveraging Conditional Generative Models in a General Explanation Framework of Classifier Decisions Martin Charachon P. Cournède C´eline Hudelot R. Ardon 17 5 0 21 Jun 2021
CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency M. Jalwana Naveed Akhtar Bennamoun Ajmal Mian 30 54 0 20 Jun 2021
NoiseGrad: Enhancing Explanations by Introducing Stochasticity to Model Weights Kirill Bykov Anna Hedström Shinichi Nakajima Marina M.-C. Höhne FAtt 17 34 0 18 Jun 2021
Guided Integrated Gradients: An Adaptive Path Method for Removing Noise A. Kapishnikov Subhashini Venugopalan Besim Avci Benjamin D. Wedin Michael Terry Tolga Bolukbasi 32 92 0 17 Jun 2021