RISE: Randomized Input Sampling for Explanation of Black-box Models

19 June 2018

Abir Das

Papers citing "RISE: Randomized Input Sampling for Explanation of Black-box Models"

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Title
Proactive Pseudo-Intervention: Causally Informed Contrastive Learning For Interpretable Vision Models Dong Wang Yuewei Yang Chenyang Tao Zhe Gan Liqun Chen Fanjie Kong Ricardo Henao Lawrence Carin 37 0 0 06 Dec 2020
BayLIME: Bayesian Local Interpretable Model-Agnostic Explanations Xingyu Zhao Wei Huang Xiaowei Huang Valentin Robu David Flynn FAtt 31 92 0 05 Dec 2020
Achievements and Challenges in Explaining Deep Learning based Computer-Aided Diagnosis Systems Adriano Lucieri Muhammad Naseer Bajwa Andreas Dengel Sheraz Ahmed 41 10 0 26 Nov 2020
Match Them Up: Visually Explainable Few-shot Image Classification Bowen Wang Liangzhi Li Manisha Verma Yuta Nakashima R. Kawasaki Hajime Nagahara FAtt 11 25 0 25 Nov 2020
Play Fair: Frame Attributions in Video Models Will Price Dima Damen FAtt 28 5 0 24 Nov 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 48 242 0 21 Nov 2020
Deep Interpretable Classification and Weakly-Supervised Segmentation of Histology Images via Max-Min Uncertainty Soufiane Belharbi Jérôme Rony Jose Dolz Ismail Ben Ayed Luke McCaffrey Eric Granger 19 52 0 14 Nov 2020
One Explanation is Not Enough: Structured Attention Graphs for Image Classification Vivswan Shitole Li Fuxin Minsuk Kahng Prasad Tadepalli Alan Fern FAtt GNN 22 38 0 13 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
Attribution Preservation in Network Compression for Reliable Network Interpretation Geondo Park J. Yang Sung Ju Hwang Eunho Yang 4 5 0 28 Oct 2020
Interpretation of NLP models through input marginalization Siwon Kim Jihun Yi Eunji Kim Sungroh Yoon MILM FAtt 22 58 0 27 Oct 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
Investigating Saturation Effects in Integrated Gradients Vivek Miglani Narine Kokhlikyan B. Alsallakh Miguel Martin Orion Reblitz-Richardson FAtt 21 23 0 23 Oct 2020
Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability Jason Phang Jungkyu Park Krzysztof J. Geras FAtt AAML 224 7 0 19 Oct 2020
Poisoned classifiers are not only backdoored, they are fundamentally broken Mingjie Sun Siddhant Agarwal J. Zico Kolter 8 25 0 18 Oct 2020
Zoom-CAM: Generating Fine-grained Pixel Annotations from Image Labels Xiangwei Shi Seyran Khademi Yun-qiang Li Jan van Gemert VLM WSOL 43 19 0 16 Oct 2020
Interpretable Machine Learning with an Ensemble of Gradient Boosting Machines A. Konstantinov Lev V. Utkin FedML AI4CE 10 138 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
IS-CAM: Integrated Score-CAM for axiomatic-based explanations Rakshit Naidu Ankita Ghosh Yash Maurya K. ShamanthRNayak Soumya Snigdha Kundu FAtt 16 46 0 06 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 6 32 0 01 Oct 2020
Where is the Model Looking At?--Concentrate and Explain the Network Attention Wenjia Xu Jiuniu Wang Yang Wang Guangluan Xu Wei Dai Yirong Wu XAI 29 17 0 29 Sep 2020
Information-Theoretic Visual Explanation for Black-Box Classifiers Jihun Yi Eunji Kim Siwon Kim Sungroh Yoon FAtt 20 6 0 23 Sep 2020
Contextual Semantic Interpretability Diego Marcos Ruth C. Fong Sylvain Lobry Rémi Flamary Nicolas Courty D. Tuia SSL 20 27 0 18 Sep 2020
SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition Liangzhi Li Bowen Wang Manisha Verma Yuta Nakashima R. Kawasaki Hajime Nagahara OCL 23 49 0 14 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 12 433 0 10 Sep 2020
Region Comparison Network for Interpretable Few-shot Image Classification Z. Xue Lixin Duan Wen Li Lin Chen Jiebo Luo 22 15 0 08 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
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
iCaps: An Interpretable Classifier via Disentangled Capsule Networks Dahuin Jung Jonghyun Lee Jihun Yi Sungroh Yoon 28 12 0 20 Aug 2020
Mitigating Dataset Imbalance via Joint Generation and Classification Aadarsh Sahoo Ankit Singh Yikang Shen Rogerio Feris Abir Das GAN 12 9 0 12 Aug 2020
Explainable Face Recognition Jonathan R. Williford Brandon B. May J. Byrne CVBM 16 71 0 03 Aug 2020
An Explainable Machine Learning Model for Early Detection of Parkinson's Disease using LIME on DaTscan Imagery Pavan Rajkumar Magesh Richard Delwin Myloth Rijo Jackson Tom FAtt 16 187 0 01 Aug 2020
Are Visual Explanations Useful? A Case Study in Model-in-the-Loop Prediction Eric Chu D. Roy Jacob Andreas FAtt LRM 13 71 0 23 Jul 2020
A Generic Visualization Approach for Convolutional Neural Networks Ahmed Taha Xitong Yang Abhinav Shrivastava L. Davis 28 8 0 19 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 24 20 0 10 Jul 2020
Counterfactual explanation of machine learning survival models M. Kovalev Lev V. Utkin CML OffRL 27 19 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 27 79 0 25 Jun 2020
A generalizable saliency map-based interpretation of model outcome Shailja Thakur S. Fischmeister AAML FAtt MILM 22 2 0 16 Jun 2020
Lung Segmentation and Nodule Detection in Computed Tomography Scan using a Convolutional Neural Network Trained Adversarially using Turing Test Loss Rakshith Sathish R. Sathish Ramanathan Sethuraman Debdoot Sheet 8 6 0 16 Jun 2020
Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey Arun Das P. Rad XAI 42 593 0 16 Jun 2020
SegNBDT: Visual Decision Rules for Segmentation Alvin Wan Daniel Ho You Song Henk Tillman Sarah Adel Bargal Joseph E. Gonzalez SSeg 9 6 0 11 Jun 2020
Black-box Explanation of Object Detectors via Saliency Maps Vitali Petsiuk R. Jain Varun Manjunatha Vlad I. Morariu Ashutosh Mehra Vicente Ordonez Kate Saenko FAtt 24 122 0 05 Jun 2020
SIDU: Similarity Difference and Uniqueness Method for Explainable AI Satya M. Muddamsetty M. N. Jahromi T. Moeslund 14 11 0 04 Jun 2020
MFPP: Morphological Fragmental Perturbation Pyramid for Black-Box Model Explanations Qing Yang Xia Zhu Jong-Kae Fwu Yun Ye Ganmei You Yuan Zhu AAML 9 20 0 04 Jun 2020
Evaluations and Methods for Explanation through Robustness Analysis Cheng-Yu Hsieh Chih-Kuan Yeh Xuanqing Liu Pradeep Ravikumar Seungyeon Kim Sanjiv Kumar Cho-Jui Hsieh XAI 15 58 0 31 May 2020
Interpretable and Accurate Fine-grained Recognition via Region Grouping Zixuan Huang Yin Li 12 138 0 21 May 2020
The Skincare project, an interactive deep learning system for differential diagnosis of malignant skin lesions. Technical Report Daniel Sonntag Fabrizio Nunnari H. Profitlich 15 12 0 19 May 2020