SmoothGrad: removing noise by adding noise

12 June 2017

Papers citing "SmoothGrad: removing noise by adding noise"

50 / 1,161 papers shown

Title
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 35 63 0 18 Dec 2020
Transformer Interpretability Beyond Attention Visualization Hila Chefer Shir Gur Lior Wolf 45 644 0 17 Dec 2020
Predicting Events in MOBA Games: Prediction, Attribution, and Evaluation Zelong Yang Yan Wang Piji Li Shaobin Lin Shuming Shi Shao-Lun Huang Wei Bi 20 12 0 17 Dec 2020
MELINDA: A Multimodal Dataset for Biomedical Experiment Method Classification Te-Lin Wu Shikhar Singh S. Paul Gully A. Burns Nanyun Peng 30 18 0 16 Dec 2020
Combining Similarity and Adversarial Learning to Generate Visual Explanation: Application to Medical Image Classification Martin Charachon C´eline Hudelot P. Cournède Camille Ruppli R. Ardon AAML GAN FAtt MedIm 8 7 0 14 Dec 2020
Demystifying Deep Neural Networks Through Interpretation: A Survey Giang Dao Minwoo Lee FaML FAtt 22 1 0 13 Dec 2020
An Empirical Study of Explainable AI Techniques on Deep Learning Models For Time Series Tasks U. Schlegel Daniela Oelke Daniel A. Keim Mennatallah El-Assady AI4TS 11 14 0 08 Dec 2020
Visualization of Supervised and Self-Supervised Neural Networks via Attribution Guided Factorization Shir Gur Ameen Ali Lior Wolf FAtt 14 37 0 03 Dec 2020
Understanding Failures of Deep Networks via Robust Feature Extraction Sahil Singla Besmira Nushi S. Shah Ece Kamar Eric Horvitz FAtt 28 83 0 03 Dec 2020
Interpretable Graph Capsule Networks for Object Recognition Jindong Gu Volker Tresp FAtt 19 36 0 03 Dec 2020
Improving Interpretability in Medical Imaging Diagnosis using Adversarial Training Andrei Margeloiu Nikola Simidjievski M. Jamnik Adrian Weller GAN AAML MedIm FAtt 21 18 0 02 Dec 2020
Towards Auditability for Fairness in Deep Learning Ivoline C. Ngong Krystal Maughan Joseph P. Near FedML 21 3 0 30 Nov 2020
Exploring the Effect of Image Enhancement Techniques on COVID-19 Detection using Chest X-rays Images Tawsifur Rahman Amith Khandakar Yazan Qiblawey Anas Tahir S. Kiranyaz ... M. Islam S. Al-Maadeed S. Zughaier Muhammad Salman Khan M. Chowdhury 16 812 0 25 Nov 2020
Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations Wolfgang Stammer P. Schramowski Kristian Kersting FAtt 14 107 0 25 Nov 2020
CAFE-GAN: Arbitrary Face Attribute Editing with Complementary Attention Feature Jeong-gi Kwak D. Han Hanseok Ko CVBM GAN 24 34 0 24 Nov 2020
Multiresolution Knowledge Distillation for Anomaly Detection Mohammadreza Salehi Niousha Sadjadi Soroosh Baselizadeh M. Rohban Hamid R. Rabiee 15 431 0 22 Nov 2020
Interpreting Super-Resolution Networks with Local Attribution Maps Jinjin Gu Chao Dong FAtt SupR 26 210 0 22 Nov 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 50 243 0 21 Nov 2020
Born Identity Network: Multi-way Counterfactual Map Generation to Explain a Classifier's Decision Kwanseok Oh Jee Seok Yoon Heung-Il Suk 15 4 0 20 Nov 2020
Certified Monotonic Neural Networks Xingchao Liu Xing Han Na Zhang Qiang Liu 24 79 0 20 Nov 2020
A Survey on the Explainability of Supervised Machine Learning Nadia Burkart Marco F. Huber FaML XAI 25 753 0 16 Nov 2020
Debiasing Convolutional Neural Networks via Meta Orthogonalization Kurtis Evan David Qiang Liu Ruth C. Fong FaML 31 3 0 15 Nov 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 24 84 0 12 Nov 2020
When Does Uncertainty Matter?: Understanding the Impact of Predictive Uncertainty in ML Assisted Decision Making S. McGrath Parth Mehta Alexandra Zytek Isaac Lage Himabindu Lakkaraju UD 8 25 0 12 Nov 2020
GANMEX: One-vs-One Attributions Guided by GAN-based Counterfactual Explanation Baselines Sheng-Min Shih Pin-Ju Tien Zohar Karnin FAtt 14 14 0 11 Nov 2020
Debugging Tests for Model Explanations Julius Adebayo M. Muelly Ilaria Liccardi Been Kim FAtt 22 179 0 10 Nov 2020
Feature Removal Is a Unifying Principle for Model Explanation Methods Ian Covert Scott M. Lundberg Su-In Lee FAtt 33 33 0 06 Nov 2020
Dynamically Sampled Nonlocal Gradients for Stronger Adversarial Attacks Leo Schwinn An Nguyen René Raab Dario Zanca Bjoern M. Eskofier Daniel Tenbrinck Martin Burger AAML 19 8 0 05 Nov 2020
Influence Patterns for Explaining Information Flow in BERT Kaiji Lu Zifan Wang Piotr (Peter) Mardziel Anupam Datta GNN 30 16 0 02 Nov 2020
Benchmarking Deep Learning Interpretability in Time Series Predictions Aya Abdelsalam Ismail Mohamed K. Gunady H. C. Bravo S. Feizi XAI AI4TS FAtt 22 168 0 26 Oct 2020
Bayesian Importance of Features (BIF) Kamil Adamczewski Frederik Harder Mijung Park FAtt 15 2 0 26 Oct 2020
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization Judy Borowski Roland S. Zimmermann Judith Schepers Robert Geirhos Thomas S. A. Wallis Matthias Bethge Wieland Brendel FAtt 47 7 0 23 Oct 2020
Towards falsifiable interpretability research Matthew L. Leavitt Ari S. Morcos AAML AI4CE 21 67 0 22 Oct 2020
Meta-trained agents implement Bayes-optimal agents Vladimir Mikulik Grégoire Delétang Tom McGrath Tim Genewein Miljan Martic Shane Legg Pedro A. Ortega OOD FedML 35 40 0 21 Oct 2020
A Survey on Deep Learning and Explainability for Automatic Report Generation from Medical Images Pablo Messina Pablo Pino Denis Parra Alvaro Soto Cecilia Besa S. Uribe Marcelo andía C. Tejos Claudia Prieto Daniel Capurro MedIm 36 62 0 20 Oct 2020
Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability Jason Phang Jungkyu Park Krzysztof J. Geras FAtt AAML 226 7 0 19 Oct 2020
A Framework to Learn with Interpretation Jayneel Parekh Pavlo Mozharovskyi Florence dÁlché-Buc AI4CE FAtt 25 30 0 19 Oct 2020
What do CNN neurons learn: Visualization & Clustering Haoyue Dai SSL 11 0 0 18 Oct 2020
FAR: A General Framework for Attributional Robustness Adam Ivankay Ivan Girardi Chiara Marchiori P. Frossard OOD 33 22 0 14 Oct 2020
Learning Propagation Rules for Attribution Map Generation Yiding Yang Jiayan Qiu Xiuming Zhang Dacheng Tao Xinchao Wang FAtt 38 17 0 14 Oct 2020
Gradient-based Analysis of NLP Models is Manipulable Junlin Wang Jens Tuyls Eric Wallace Sameer Singh AAML FAtt 25 58 0 12 Oct 2020
WHO 2016 subtyping and automated segmentation of glioma using multi-task deep learning S. V. D. Voort Fatih Incekara M. Wijnenga G. Kapsas R. Gahrmann ... A. Vincent W. Niessen M. Bent M. Smits S. Klein 9 7 0 09 Oct 2020
Visualizing Color-wise Saliency of Black-Box Image Classification Models Yuhki Hatakeyama Hiroki Sakuma Yoshinori Konishi Kohei Suenaga FAtt 22 3 0 06 Oct 2020
Remembering for the Right Reasons: Explanations Reduce Catastrophic Forgetting Sayna Ebrahimi Suzanne Petryk Akash Gokul William Gan Joseph E. Gonzalez Marcus Rohrbach Trevor Darrell CLL 37 45 0 04 Oct 2020
Explaining Convolutional Neural Networks through Attribution-Based Input Sampling and Block-Wise Feature Aggregation S. Sattarzadeh M. Sudhakar Anthony Lem Shervin Mehryar K. N. Plataniotis Jongseong Jang Hyunwoo J. Kim Yeonjeong Jeong Sang-Min Lee Kyunghoon Bae FAtt XAI 8 32 0 01 Oct 2020
Trustworthy Convolutional Neural Networks: A Gradient Penalized-based Approach Nicholas F Halliwell Freddy Lecue FAtt 25 9 0 29 Sep 2020
Improving Interpretability for Computer-aided Diagnosis tools on Whole Slide Imaging with Multiple Instance Learning and Gradient-based Explanations Antoine Pirovano H. Heuberger Sylvain Berlemont Saïd Ladjal Isabelle Bloch 21 12 0 29 Sep 2020
Quantitative and Qualitative Evaluation of Explainable Deep Learning Methods for Ophthalmic Diagnosis Amitojdeep Singh J. Balaji M. Rasheed Varadharajan Jayakumar R. Raman Vasudevan Lakshminarayanan BDL XAI FAtt 16 29 0 26 Sep 2020
Information-Theoretic Visual Explanation for Black-Box Classifiers Jihun Yi Eunji Kim Siwon Kim Sungroh Yoon FAtt 25 6 0 23 Sep 2020
Introspective Learning by Distilling Knowledge from Online Self-explanation Jindong Gu Zhiliang Wu Volker Tresp 17 3 0 19 Sep 2020