SmoothGrad: removing noise by adding noise

12 June 2017

Papers citing "SmoothGrad: removing noise by adding noise"

50 / 1,161 papers shown

Title
A Test Statistic Estimation-based Approach for Establishing Self-interpretable CNN-based Binary Classifiers S. Sengupta M. Anastasio MedIm 33 6 0 13 Mar 2023
RotoGBML: Towards Out-of-Distribution Generalization for Gradient-Based Meta-Learning Min Zhang Zifeng Zhuang Zhitao Wang Donglin Wang Wen-Bin Li 46 5 0 12 Mar 2023
Use Perturbations when Learning from Explanations Juyeon Heo Vihari Piratla Matthew Wicker Adrian Weller AAML 40 1 0 11 Mar 2023
Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey Yulong Wang Tong Sun Shenghong Li Xinnan Yuan W. Ni Ekram Hossain H. Vincent Poor AAML 31 18 0 11 Mar 2023
Towards Trust of Explainable AI in Thyroid Nodule Diagnosis Hung Truong Thanh Nguyen Van Binh Truong V. Nguyen Quoc Hung Cao Quoc Khanh Nguyen 14 13 0 08 Mar 2023
CoRTX: Contrastive Framework for Real-time Explanation Yu-Neng Chuang Guanchu Wang Fan Yang Quan-Gen Zhou Pushkar Tripathi Xuanting Cai Xia Hu 46 20 0 05 Mar 2023
DeepSeer: Interactive RNN Explanation and Debugging via State Abstraction Zhijie Wang Yuheng Huang D. Song Lei Ma Tianyi Zhang HAI 58 5 0 02 Mar 2023
Feature Perturbation Augmentation for Reliable Evaluation of Importance Estimators in Neural Networks L. Brocki N. C. Chung FAtt AAML 51 11 0 02 Mar 2023
Finding the right XAI method -- A Guide for the Evaluation and Ranking of Explainable AI Methods in Climate Science P. Bommer M. Kretschmer Anna Hedström Dilyara Bareeva Marina M.-C. Höhne 54 38 0 01 Mar 2023
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective Xiwei Xuan Ziquan Deng Hsuan-Tien Lin Z. Kong Kwan-Liu Ma AAML FAtt 37 2 0 01 Mar 2023
Single Image Backdoor Inversion via Robust Smoothed Classifiers Mingjie Sun Zico Kolter AAML 23 12 0 01 Mar 2023
Multi-Layer Attention-Based Explainability via Transformers for Tabular Data Andrea Trevino Gavito Diego Klabjan J. Utke LMTD 25 3 0 28 Feb 2023
MDF-Net for abnormality detection by fusing X-rays with clinical data Chih-Jou Hsieh Isabel Blanco Nobre Sandra Costa Sousa Chun Ouyang M. Brereton Jacinto C. Nascimento Joaquim A. Jorge Catarina Moreira 18 8 0 26 Feb 2023
Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation N. Jethani A. Saporta Rajesh Ranganath FAtt 31 11 0 24 Feb 2023
Frequency and Scale Perspectives of Feature Extraction Liangqi Zhang Yihao Luo Xiang Cao Haibo Shen Tianjiang Wang 21 0 0 24 Feb 2023
The Generalizability of Explanations Hanxiao Tan FAtt 18 1 0 23 Feb 2023
Non-Uniform Interpolation in Integrated Gradients for Low-Latency Explainable-AI Ashwin Bhat A. Raychowdhury 25 4 0 22 Feb 2023
TAX: Tendency-and-Assignment Explainer for Semantic Segmentation with Multi-Annotators Yuan Cheng Zu-Yun Shiau Fu-En Yang Yu-Chiang Frank Wang 39 2 0 19 Feb 2023
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus Anna Hedström P. Bommer Kristoffer K. Wickstrom Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne 37 21 0 14 Feb 2023
On The Coherence of Quantitative Evaluation of Visual Explanations Benjamin Vandersmissen José Oramas XAI FAtt 36 3 0 14 Feb 2023
Interpretable Diversity Analysis: Visualizing Feature Representations In Low-Cost Ensembles Tim Whitaker L. D. Whitley 13 0 0 12 Feb 2023
Towards a Deeper Understanding of Concept Bottleneck Models Through End-to-End Explanation Jack Furby Daniel Cunnington Dave Braines Alun D. Preece 22 6 0 07 Feb 2023
PAMI: partition input and aggregate outputs for model interpretation Wei Shi Wentao Zhang Weishi Zheng Ruixuan Wang FAtt 26 3 0 07 Feb 2023
Efficient XAI Techniques: A Taxonomic Survey Yu-Neng Chuang Guanchu Wang Fan Yang Zirui Liu Xuanting Cai Mengnan Du Xia Hu 24 32 0 07 Feb 2023
LAVA: Granular Neuron-Level Explainable AI for Alzheimer's Disease Assessment from Fundus Images Nooshin Yousefzadeh Charlie Tran Adolfo Ramirez-Zamora Jinghua Chen R. Fang My T. Thai 32 1 0 06 Feb 2023
Variational Information Pursuit for Interpretable Predictions Aditya Chattopadhyay Kwan Ho Ryan Chan B. Haeffele D. Geman René Vidal DRL 24 11 0 06 Feb 2023
Interpreting Robustness Proofs of Deep Neural Networks Debangshu Banerjee Avaljot Singh Gagandeep Singh AAML 29 5 0 31 Jan 2023
A Survey of Explainable AI in Deep Visual Modeling: Methods and Metrics Naveed Akhtar XAI VLM 35 7 0 31 Jan 2023
Diffusion Models as Artists: Are we Closing the Gap between Humans and Machines? Victor Boutin Thomas Fel Lakshya Singhal Rishav Mukherji Akash Nagaraj Julien Colin Thomas Serre DiffM 30 6 0 27 Jan 2023
Certified Interpretability Robustness for Class Activation Mapping Alex Gu Tsui-Wei Weng Pin-Yu Chen Sijia Liu Lucani E. Daniel AAML 34 2 0 26 Jan 2023
Interpretable Out-Of-Distribution Detection Using Pattern Identification Romain Xu-Darme Julien Girard-Satabin Darryl Hond Gabriele Incorvaia Zakaria Chihani OODD 30 3 0 24 Jan 2023
Sanity checks and improvements for patch visualisation in prototype-based image classification Romain Xu-Darme Georges Quénot Zakaria Chihani M. Rousset 10 3 0 20 Jan 2023
Interpreting CNN Predictions using Conditional Generative Adversarial Networks Akash Guna Raul Benitez Sikha GAN 13 4 0 19 Jan 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 41 22 0 17 Jan 2023
Negative Flux Aggregation to Estimate Feature Attributions X. Li Deng Pan Chengyin Li Yao Qiang D. Zhu FAtt 8 6 0 17 Jan 2023
Rationalizing Predictions by Adversarial Information Calibration Lei Sha Oana-Maria Camburu Thomas Lukasiewicz 27 4 0 15 Jan 2023
Uncertainty Quantification for Local Model Explanations Without Model Access Surin Ahn J. Grana Yafet Tamene Kristian Holsheimer FAtt 31 0 0 13 Jan 2023
MoreauGrad: Sparse and Robust Interpretation of Neural Networks via Moreau Envelope Jingwei Zhang Farzan Farnia UQCV 36 3 0 08 Jan 2023
Explainability and Robustness of Deep Visual Classification Models Jindong Gu AAML 47 2 0 03 Jan 2023
NeuroExplainer: Fine-Grained Attention Decoding to Uncover Cortical Development Patterns of Preterm Infants Chen Xue Fan Wang Yuanzhuo Zhu Hui Li Deyu Meng Dinggang Shen C. Lian 52 2 0 01 Jan 2023
ExploreADV: Towards exploratory attack for Neural Networks Tianzuo Luo Yuyi Zhong S. Khoo AAML 24 1 0 01 Jan 2023
Provable Robust Saliency-based Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie AAML FAtt 38 0 0 28 Dec 2022
DeepCuts: Single-Shot Interpretability based Pruning for BERT Jasdeep Singh Grover Bhavesh Gawri R. Manku 33 1 0 27 Dec 2022
Key Feature Replacement of In-Distribution Samples for Out-of-Distribution Detection Jaeyoung Kim Seo Taek Kong Dongbin Na Kyu-Hwan Jung OODD 24 4 0 26 Dec 2022
Impossibility Theorems for Feature Attribution Blair Bilodeau Natasha Jaques Pang Wei Koh Been Kim FAtt 20 68 0 22 Dec 2022
DExT: Detector Explanation Toolkit Deepan Padmanabhan Paul G. Plöger Octavio Arriaga Matias Valdenegro-Toro 38 2 0 21 Dec 2022
Bort: Towards Explainable Neural Networks with Bounded Orthogonal Constraint Borui Zhang Wenzhao Zheng Jie Zhou Jiwen Lu AAML 27 7 0 18 Dec 2022
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 31 18 0 16 Dec 2022
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 40 14 0 13 Dec 2022
Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods Ming-Xiu Jiang Saeed Khorram Li Fuxin FAtt 27 9 0 13 Dec 2022