SmoothGrad: removing noise by adding noise

12 June 2017

Papers citing "SmoothGrad: removing noise by adding noise"

50 / 1,161 papers shown

Title
Reconstructing Actions To Explain Deep Reinforcement Learning Xuan Chen Zifan Wang Yucai Fan Bonan Jin Piotr (Peter) Mardziel Carlee Joe-Wong Anupam Datta FAtt 13 2 0 17 Sep 2020
Captum: A unified and generic model interpretability library for PyTorch Narine Kokhlikyan Vivek Miglani Miguel Martin Edward Wang B. Alsallakh ... Alexander Melnikov Natalia Kliushkina Carlos Araya Siqi Yan Orion Reblitz-Richardson FAtt 29 822 0 16 Sep 2020
Are Interpretations Fairly Evaluated? A Definition Driven Pipeline for Post-Hoc Interpretability Ninghao Liu Yunsong Meng Xia Hu Tie Wang Bo Long XAI FAtt 23 7 0 16 Sep 2020
Beyond Individualized Recourse: Interpretable and Interactive Summaries of Actionable Recourses Kaivalya Rawal Himabindu Lakkaraju 27 11 0 15 Sep 2020
MeLIME: Meaningful Local Explanation for Machine Learning Models T. Botari Frederik Hvilshoj Rafael Izbicki A. Carvalho AAML FAtt 30 16 0 12 Sep 2020
Understanding the Role of Individual Units in a Deep Neural Network David Bau Jun-Yan Zhu Hendrik Strobelt Àgata Lapedriza Bolei Zhou Antonio Torralba GAN 14 436 0 10 Sep 2020
Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent Ricardo Bigolin Lanfredi Joyce D. Schroeder Tolga Tasdizen 27 11 0 10 Sep 2020
How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks Thomas Fel David Vigouroux Rémi Cadène Thomas Serre XAI FAtt 34 31 0 07 Sep 2020
Quantifying Explainability of Saliency Methods in Deep Neural Networks with a Synthetic Dataset Erico Tjoa Cuntai Guan XAI FAtt 16 27 0 07 Sep 2020
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring Nijat Mehdiyev Peter Fettke AI4TS 25 55 0 04 Sep 2020
Estimating Example Difficulty Using Variance of Gradients Chirag Agarwal Daniel D'souza Sara Hooker 213 108 0 26 Aug 2020
How Useful Are the Machine-Generated Interpretations to General Users? A Human Evaluation on Guessing the Incorrectly Predicted Labels Hua Shen Ting-Hao 'Kenneth' Huang FAtt HAI 17 56 0 26 Aug 2020
Making Neural Networks Interpretable with Attribution: Application to Implicit Signals Prediction Darius Afchar Romain Hennequin FAtt XAI 39 16 0 26 Aug 2020
DNN2LR: Interpretation-inspired Feature Crossing for Real-world Tabular Data Zhaocheng Liu Qiang Liu Haoli Zhang Yuntian Chen 19 12 0 22 Aug 2020
A Unified Taylor Framework for Revisiting Attribution Methods Huiqi Deng Na Zou Mengnan Du Weifu Chen Guo-Can Feng Xia Hu FAtt TDI 40 21 0 21 Aug 2020
Explainable Recommender Systems via Resolving Learning Representations Ninghao Liu Yong Ge Li Li Xia Hu Rui Chen Soo-Hyun Choi 24 24 0 21 Aug 2020
iCaps: An Interpretable Classifier via Disentangled Capsule Networks Dahuin Jung Jonghyun Lee Jihun Yi Sungroh Yoon 33 12 0 20 Aug 2020
Intelligence plays dice: Stochasticity is essential for machine learning M. Sabuncu 32 6 0 17 Aug 2020
Survey of XAI in digital pathology Milda Pocevičiūtė Gabriel Eilertsen Claes Lundström 14 56 0 14 Aug 2020
Can We Trust Your Explanations? Sanity Checks for Interpreters in Android Malware Analysis Ming Fan Wenying Wei Xiaofei Xie Yang Liu X. Guan Ting Liu FAtt AAML 22 36 0 13 Aug 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 26 162 0 11 Aug 2020
Informative Dropout for Robust Representation Learning: A Shape-bias Perspective Baifeng Shi Dinghuai Zhang Qi Dai Zhanxing Zhu Yadong Mu Jingdong Wang OOD 27 111 0 10 Aug 2020
Assessing the (Un)Trustworthiness of Saliency Maps for Localizing Abnormalities in Medical Imaging N. Arun N. Gaw P. Singh Ken Chang M. Aggarwal ... J. Patel M. Gidwani Julius Adebayo M. D. Li Jayashree Kalpathy-Cramer FAtt 27 109 0 06 Aug 2020
Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs Ruigang Fu Qingyong Hu Xiaohu Dong Yulan Guo Yinghui Gao Biao Li FAtt 24 266 0 05 Aug 2020
Weakly-Supervised Cell Tracking via Backward-and-Forward Propagation Kazuya Nishimura Junya Hayashida Chenyang Wang Dai Fei Elmer Ker Ryoma Bise 26 17 0 30 Jul 2020
Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM Guohao Yu A. Zare Weihuang Xu R. Matamala J. Reyes‐Cabrera F. Fritschi T. Juenger 14 12 0 30 Jul 2020
Reliable Tuberculosis Detection using Chest X-ray with Deep Learning, Segmentation and Visualization Tawsifur Rahman Amith Khandakar M. A. Kadir K. R. Islam Khandaker F. Islam ... Tahir Hamid M. Islam Z. Mahbub M. Ayari M. Chowdhury 22 358 0 29 Jul 2020
Feature visualization of Raman spectrum analysis with deep convolutional neural network Masashi Fukuhara Kazuhiko Fujiwara Y. Maruyama H. Itoh 6 62 0 27 Jul 2020
Are Visual Explanations Useful? A Case Study in Model-in-the-Loop Prediction Eric Chu D. Roy Jacob Andreas FAtt LRM 16 71 0 23 Jul 2020
Deep Active Learning by Model Interpretability Qiang Liu Zhaocheng Liu Xiaofang Zhu Yeliang Xiu 24 4 0 23 Jul 2020
Pattern-Guided Integrated Gradients Robert Schwarzenberg Steffen Castle 20 1 0 21 Jul 2020
A Generic Visualization Approach for Convolutional Neural Networks Ahmed Taha Xitong Yang Abhinav Shrivastava L. Davis 31 8 0 19 Jul 2020
Multi-Stage Influence Function Hongge Chen Si Si Yongqian Li Ciprian Chelba Sanjiv Kumar Duane S. Boning Cho-Jui Hsieh TDI 25 17 0 17 Jul 2020
Sequential Explanations with Mental Model-Based Policies A. Yeung Shalmali Joshi Joseph Jay Williams Frank Rudzicz FAtt LRM 31 15 0 17 Jul 2020
Deep Learning in Protein Structural Modeling and Design Wenhao Gao S. Mahajan Jeremias Sulam Jeffrey J. Gray 29 159 0 16 Jul 2020
Concept Learners for Few-Shot Learning Kaidi Cao Maria Brbic J. Leskovec VLM OffRL 30 4 0 14 Jul 2020
A simple defense against adversarial attacks on heatmap explanations Laura Rieger Lars Kai Hansen FAtt AAML 33 37 0 13 Jul 2020
Usefulness of interpretability methods to explain deep learning based plant stress phenotyping Koushik Nagasubramanian Asheesh K. Singh Arti Singh S. Sarkar Baskar Ganapathysubramanian FAtt 19 16 0 11 Jul 2020
Scientific Discovery by Generating Counterfactuals using Image Translation Arunachalam Narayanaswamy Subhashini Venugopalan D. Webster L. Peng G. Corrado ... Abigail E. Huang Siva Balasubramanian Michael P. Brenner Phil Q. Nelson A. Varadarajan DiffM MedIm 30 20 0 10 Jul 2020
PointMask: Towards Interpretable and Bias-Resilient Point Cloud Processing Saeid Asgari Taghanaki Kaveh Hassani P. Jayaraman Amir Hosein Khas Ahmadi Tonya Custis 3DPC 12 8 0 09 Jul 2020
Evaluation for Weakly Supervised Object Localization: Protocol, Metrics, and Datasets Junsuk Choe Seong Joon Oh Sanghyuk Chun Seungho Lee Zeynep Akata Hyunjung Shim WSOL 352 23 0 08 Jul 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 30 626 0 01 Jul 2020
Scaling Symbolic Methods using Gradients for Neural Model Explanation Subham S. Sahoo Subhashini Venugopalan Li Li Rishabh Singh Patrick F. Riley FAtt 8 8 0 29 Jun 2020
Invertible Concept-based Explanations for CNN Models with Non-negative Concept Activation Vectors Ruihan Zhang Prashan Madumal Tim Miller Krista A. Ehinger Benjamin I. P. Rubinstein FAtt 24 94 0 27 Jun 2020
BERTology Meets Biology: Interpreting Attention in Protein Language Models Jesse Vig Ali Madani L. Varshney Caiming Xiong R. Socher Nazneen Rajani 29 288 0 26 Jun 2020
Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy Sijia Liu Gaoyuan Zhang Cynthia Liu Pin-Yu Chen Shiyu Chang Luca Daniel AAML FAtt 27 66 0 26 Jun 2020
SS-CAM: Smoothed Score-CAM for Sharper Visual Feature Localization Haofan Wang Rakshit Naidu J. Michael Soumya Snigdha Kundu FAtt 30 79 0 25 Jun 2020
Model Explanations with Differential Privacy Neel Patel Reza Shokri Yair Zick SILM FedML 28 32 0 16 Jun 2020
Rethinking the Role of Gradient-Based Attribution Methods for Model Interpretability Suraj Srinivas F. Fleuret FAtt 18 1 0 16 Jun 2020
On Saliency Maps and Adversarial Robustness Puneet Mangla Vedant Singh V. Balasubramanian AAML 24 16 0 14 Jun 2020