SmoothGrad: removing noise by adding noise

12 June 2017

Papers citing "SmoothGrad: removing noise by adding noise"

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Title
Toward Explainable AI for Regression Models S. Letzgus Patrick Wagner Jonas Lederer Wojciech Samek Klaus-Robert Muller G. Montavon XAI 36 63 0 21 Dec 2021
RELAX: Representation Learning Explainability Kristoffer Wickstrøm Daniel J. Trosten Sigurd Løkse Ahcène Boubekki Karl Øyvind Mikalsen Michael C. Kampffmeyer Robert Jenssen FAtt 13 14 0 19 Dec 2021
Explain, Edit, and Understand: Rethinking User Study Design for Evaluating Model Explanations Siddhant Arora Danish Pruthi Norman M. Sadeh William W. Cohen Zachary Chase Lipton Graham Neubig FAtt 40 38 0 17 Dec 2021
Disentangled representations: towards interpretation of sex determination from hip bone K. Zou S. Faisan F. Heitz Marie Epain P. Croisille L. Fanton S. Valette 3DH DRL 29 3 0 17 Dec 2021
High Fidelity Visualization of What Your Self-Supervised Representation Knows About Florian Bordes Randall Balestriero Pascal Vincent DiffM 25 61 0 16 Dec 2021
Towards Explainable Artificial Intelligence in Banking and Financial Services Ambreen Hanif 22 9 0 14 Dec 2021
DGL-GAN: Discriminator Guided Learning for GAN Compression Yuesong Tian Li Shen Xiang Tian Dacheng Tao Zhifeng Li Wei Liu Yao-wu Chen 31 0 0 13 Dec 2021
Latent Space Explanation by Intervention Itai Gat Guy Lorberbom Idan Schwartz Tamir Hazan BDL 33 14 0 09 Dec 2021
What I Cannot Predict, I Do Not Understand: A Human-Centered Evaluation Framework for Explainability Methods Julien Colin Thomas Fel Rémi Cadène Thomas Serre 33 101 0 06 Dec 2021
Making a Bird AI Expert Work for You and Me Dongliang Chang Kaiyue Pang Ruoyi Du Zhanyu Ma Yi-Zhe Song Jun Guo 70 10 0 06 Dec 2021
Visual Persuasion in COVID-19 Social Media Content: A Multi-Modal Characterization Mesut Erhan Unal Adriana Kovashka Wen-Ting Chung Yu-Ru Lin 21 4 0 05 Dec 2021
Deformable ProtoPNet: An Interpretable Image Classifier Using Deformable Prototypes Jonathan Donnelly A. Barnett Chaofan Chen 3DH 38 127 0 29 Nov 2021
Improving Deep Learning Interpretability by Saliency Guided Training Aya Abdelsalam Ismail H. C. Bravo S. Feizi FAtt 31 80 0 29 Nov 2021
ExCon: Explanation-driven Supervised Contrastive Learning for Image Classification Zhibo Zhang Jongseong Jang C. Trabelsi Ruiwen Li Scott Sanner Yeonjeong Jeong Dongsub Shim 14 4 0 28 Nov 2021
Learning a Weight Map for Weakly-Supervised Localization Tal Shaharabany Lior Wolf WSOL SSL 18 1 0 28 Nov 2021
Evaluation of Interpretability for Deep Learning algorithms in EEG Emotion Recognition: A case study in Autism J. M. M. Torres Sara E. Medina-DeVilliers T. Clarkson M. Lerner Giuseppe Riccardi 35 34 0 25 Nov 2021
SPINE: Soft Piecewise Interpretable Neural Equations Jasdeep Singh Grover Harsh Minesh Domadia Rajashree Tapase Grishma Sharma 21 0 0 20 Nov 2021
A Robust Unsupervised Ensemble of Feature-Based Explanations using Restricted Boltzmann Machines V. Borisov Johannes Meier J. V. D. Heuvel Hamed Jalali Gjergji Kasneci FAtt 47 5 0 14 Nov 2021
Beyond Importance Scores: Interpreting Tabular ML by Visualizing Feature Semantics Amirata Ghorbani Dina Berenbaum Maor Ivgi Yuval Dafna James Zou FAtt 28 8 0 10 Nov 2021
Defense Against Explanation Manipulation Ruixiang Tang Ninghao Liu Fan Yang Na Zou Xia Hu AAML 46 11 0 08 Nov 2021
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis Thomas Fel Rémi Cadène Mathieu Chalvidal Matthieu Cord David Vigouroux Thomas Serre MLAU FAtt AAML 120 61 0 07 Nov 2021
Explainable Deep Reinforcement Learning for Portfolio Management: An Empirical Approach Mao Guan Xiao-Yang Liu AIFin AI4TS 27 20 0 07 Nov 2021
Explaining neural network predictions of material strength Ian Palmer T. Nathan Mundhenk B. J. Gallagher Yong Han 21 2 0 05 Nov 2021
Pareto Adversarial Robustness: Balancing Spatial Robustness and Sensitivity-based Robustness Ke Sun Mingjie Li Zhouchen Lin AAML 27 2 0 03 Nov 2021
Gradient Frequency Modulation for Visually Explaining Video Understanding Models Xinmiao Lin Wentao Bao Matthew Wright Yu Kong FAtt AAML 30 2 0 01 Nov 2021
Transparency of Deep Neural Networks for Medical Image Analysis: A Review of Interpretability Methods Zohaib Salahuddin Henry C. Woodruff A. Chatterjee Philippe Lambin 29 306 0 01 Nov 2021
ST-ABN: Visual Explanation Taking into Account Spatio-temporal Information for Video Recognition Masahiro Mitsuhara Tsubasa Hirakawa Takayoshi Yamashita H. Fujiyoshi 27 1 0 29 Oct 2021
Revisiting Sanity Checks for Saliency Maps G. Yona D. Greenfeld AAML FAtt 30 25 0 27 Oct 2021
A Unified Survey on Anomaly, Novelty, Open-Set, and Out-of-Distribution Detection: Solutions and Future Challenges Mohammadreza Salehi Hossein Mirzaei Dan Hendrycks Yixuan Li M. Rohban Mohammad Sabokrou OOD 38 191 0 26 Oct 2021
ProtoShotXAI: Using Prototypical Few-Shot Architecture for Explainable AI Samuel Hess G. Ditzler AAML 33 1 0 22 Oct 2021
Pixel-Level Face Image Quality Assessment for Explainable Face Recognition Philipp Terhörst Marco Huber Naser Damer Florian Kirchbuchner Kiran Raja Arjan Kuijper CVBM 31 26 0 21 Oct 2021
Interpreting Deep Learning Models in Natural Language Processing: A Review Xiaofei Sun Diyi Yang Xiaoya Li Tianwei Zhang Yuxian Meng Han Qiu Guoyin Wang Eduard H. Hovy Jiwei Li 24 45 0 20 Oct 2021
TorchEsegeta: Framework for Interpretability and Explainability of Image-based Deep Learning Models S. Chatterjee Arnab Das Chirag Mandal Budhaditya Mukhopadhyay Manish Vipinraj Aniruddh Shukla R. Rao Chompunuch Sarasaen Oliver Speck A. Nürnberger MedIm 42 14 0 16 Oct 2021
Robustness of different loss functions and their impact on networks learning capability Vishal Rajput OOD AAML 20 14 0 15 Oct 2021
Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings Jan Macdonald Mathieu Besançon Sebastian Pokutta 32 12 0 15 Oct 2021
When saliency goes off on a tangent: Interpreting Deep Neural Networks with nonlinear saliency maps Jan Rosenzweig Zoran Cvetkovic I. Rosenzweig FAtt 29 0 0 13 Oct 2021
A Rate-Distortion Framework for Explaining Black-box Model Decisions Stefan Kolek Duc Anh Nguyen Ron Levie Joan Bruna Gitta Kutyniok 35 15 0 12 Oct 2021
TSGB: Target-Selective Gradient Backprop for Probing CNN Visual Saliency Lin Cheng Pengfei Fang Yanjie Liang Liao Zhang Chunhua Shen Hanzi Wang FAtt 27 11 0 11 Oct 2021
Salient ImageNet: How to discover spurious features in Deep Learning? Sahil Singla S. Feizi AAML VLM 29 115 0 08 Oct 2021
Explainability-Aware One Point Attack for Point Cloud Neural Networks Hanxiao Tan Helena Kotthaus 3DPC AAML 24 11 0 08 Oct 2021
Cartoon Explanations of Image Classifiers Stefan Kolek Duc Anh Nguyen Ron Levie Joan Bruna Gitta Kutyniok FAtt 40 15 0 07 Oct 2021
Deep Synoptic Monte Carlo Planning in Reconnaissance Blind Chess Gregory Clark 38 9 0 05 Oct 2021
Focus! Rating XAI Methods and Finding Biases Anna Arias-Duart Ferran Parés Dario Garcia-Gasulla Victor Gimenez-Abalos 26 32 0 28 Sep 2021
Discriminative Attribution from Counterfactuals N. Eckstein A. S. Bates G. Jefferis Jan Funke FAtt CML 27 1 0 28 Sep 2021
Time Series Model Attribution Visualizations as Explanations U. Schlegel Daniel A. Keim TDI BDL FAtt AI4TS XAI 53 15 0 27 Sep 2021
DeepAID: Interpreting and Improving Deep Learning-based Anomaly Detection in Security Applications Dongqi Han Zhiliang Wang Wenqi Chen Ying Zhong Su Wang Han Zhang Jiahai Yang Xingang Shi Xia Yin AAML 24 76 0 23 Sep 2021
Explainability Requires Interactivity Matthias Kirchler M. Graf Marius Kloft C. Lippert FAtt AAML HAI 35 1 0 16 Sep 2021
CounterNet: End-to-End Training of Prediction Aware Counterfactual Explanations Hangzhi Guo T. Nguyen A. Yadav OffRL 24 14 0 15 Sep 2021
Attention Weights in Transformer NMT Fail Aligning Words Between Sequences but Largely Explain Model Predictions Javier Ferrando Marta R. Costa-jussá 22 13 0 13 Sep 2021
Saliency Guided Experience Packing for Replay in Continual Learning Gobinda Saha Kaushik Roy VLM KELM CLL 99 22 0 10 Sep 2021