Sanity Checks for Saliency Maps

8 October 2018

Justin Gilmer

Papers citing "Sanity Checks for Saliency Maps"

50 / 302 papers shown

Title
Towards Out-Of-Distribution Generalization: A Survey Jiashuo Liu Zheyan Shen Yue He Xingxuan Zhang Renzhe Xu Han Yu Peng Cui CML OOD 31 515 0 31 Aug 2021
Feature Importance in a Deep Learning Climate Emulator Wei-ping Xu Xihaier Luo Yihui Ren Ji Hwan Park Shinjae Yoo B. Nadiga FAtt AI4TS 29 3 0 27 Aug 2021
Longitudinal Distance: Towards Accountable Instance Attribution Rosina O. Weber Prateek Goel S. Amiri G. Simpson 11 0 0 23 Aug 2021
GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks Lucie Charlotte Magister Dmitry Kazhdan Vikash Singh Pietro Lió 27 48 0 25 Jul 2021
Robust Counterfactual Explanations on Graph Neural Networks Mohit Bajaj Lingyang Chu Zihui Xue J. Pei Lanjun Wang P. C. Lam Yong Zhang OOD 35 96 0 08 Jul 2021
Challenges for machine learning in clinical translation of big data imaging studies Nicola K. Dinsdale Emma Bluemke V. Sundaresan M. Jenkinson Stephen Smith Ana I. L. Namburete AI4CE 32 41 0 07 Jul 2021
Knowledge-Grounded Self-Rationalization via Extractive and Natural Language Explanations Bodhisattwa Prasad Majumder Oana-Maria Camburu Thomas Lukasiewicz Julian McAuley 23 35 0 25 Jun 2021
Evaluation of Saliency-based Explainability Method Sam Zabdiel Sunder Samuel V. Kamakshi Namrata Lodhi N. C. Krishnan FAtt XAI 21 12 0 24 Jun 2021
Synthetic Benchmarks for Scientific Research in Explainable Machine Learning Yang Liu Sujay Khandagale Colin White W. Neiswanger 28 65 0 23 Jun 2021
CAMERAS: Enhanced Resolution And Sanity preserving Class Activation Mapping for image saliency M. Jalwana Naveed Akhtar Bennamoun Ajmal Saeed Mian 22 54 0 20 Jun 2021
Characterizing the risk of fairwashing Ulrich Aivodji Hiromi Arai Sébastien Gambs Satoshi Hara 20 27 0 14 Jun 2021
Certification of embedded systems based on Machine Learning: A survey Guillaume Vidot Christophe Gabreau I. Ober Iulian Ober 6 12 0 14 Jun 2021
3DB: A Framework for Debugging Computer Vision Models Guillaume Leclerc Hadi Salman Andrew Ilyas Sai H. Vemprala Logan Engstrom ... Pengchuan Zhang Shibani Santurkar Greg Yang Ashish Kapoor A. Madry 38 40 0 07 Jun 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks Eric Wong Shibani Santurkar A. Madry FAtt 20 88 0 11 May 2021
Do Feature Attribution Methods Correctly Attribute Features? Yilun Zhou Serena Booth Marco Tulio Ribeiro J. Shah FAtt XAI 22 132 0 27 Apr 2021
Exploiting Explanations for Model Inversion Attacks Xu Zhao Wencan Zhang Xiao Xiao Brian Y. Lim MIACV 21 82 0 26 Apr 2021
Towards Rigorous Interpretations: a Formalisation of Feature Attribution Darius Afchar Romain Hennequin Vincent Guigue FAtt 29 20 0 26 Apr 2021
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case Natalia Díaz Rodríguez Alberto Lamas Jules Sanchez Gianni Franchi Ivan Donadello S. Tabik David Filliat P. Cruz Rosana Montes Francisco Herrera 47 77 0 24 Apr 2021
Towards a Collective Agenda on AI for Earth Science Data Analysis D. Tuia R. Roscher Jan Dirk Wegner Nathan Jacobs Xiaoxiang Zhu Gustau Camps-Valls AI4CE 39 68 0 11 Apr 2021
Deep Interpretable Models of Theory of Mind Ini Oguntola Dana Hughes Katia P. Sycara HAI 25 23 0 07 Apr 2021
Evaluating explainable artificial intelligence methods for multi-label deep learning classification tasks in remote sensing Ioannis Kakogeorgiou Konstantinos Karantzalos XAI 23 118 0 03 Apr 2021
Model Selection's Disparate Impact in Real-World Deep Learning Applications Jessica Zosa Forde A. Feder Cooper Kweku Kwegyir-Aggrey Chris De Sa Michael Littman 11 22 0 01 Apr 2021
Explaining COVID-19 and Thoracic Pathology Model Predictions by Identifying Informative Input Features Ashkan Khakzar Yang Zhang W. Mansour Yuezhi Cai Yawei Li Yucheng Zhang Seong Tae Kim Nassir Navab FAtt 44 17 0 01 Apr 2021
Group-CAM: Group Score-Weighted Visual Explanations for Deep Convolutional Networks Qing-Long Zhang Lu Rao Yubin Yang 11 58 0 25 Mar 2021
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography A. Barnett F. Schwartz Chaofan Tao Chaofan Chen Yinhao Ren J. Lo Cynthia Rudin 31 133 0 23 Mar 2021
Robust Models Are More Interpretable Because Attributions Look Normal Zifan Wang Matt Fredrikson Anupam Datta OOD FAtt 28 25 0 20 Mar 2021
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges Cynthia Rudin Chaofan Chen Zhi Chen Haiyang Huang Lesia Semenova Chudi Zhong FaML AI4CE LRM 53 651 0 20 Mar 2021
Beyond Trivial Counterfactual Explanations with Diverse Valuable Explanations Pau Rodríguez López Massimo Caccia Alexandre Lacoste L. Zamparo I. Laradji Laurent Charlin David Vazquez AAML 29 55 0 18 Mar 2021
Neural Network Attribution Methods for Problems in Geoscience: A Novel Synthetic Benchmark Dataset Antonios Mamalakis I. Ebert‐Uphoff E. Barnes OOD 23 75 0 18 Mar 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics Valerie Chen Jeffrey Li Joon Sik Kim Gregory Plumb Ameet Talwalkar 24 29 0 10 Mar 2021
Detecting Spurious Correlations with Sanity Tests for Artificial Intelligence Guided Radiology Systems U. Mahmood Robik Shrestha D. Bates L. Mannelli G. Corrias Y. Erdi Christopher Kanan 16 16 0 04 Mar 2021
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations N. Jethani Mukund Sudarshan Yindalon Aphinyanagphongs Rajesh Ranganath FAtt 82 70 0 02 Mar 2021
Do Input Gradients Highlight Discriminative Features? Harshay Shah Prateek Jain Praneeth Netrapalli AAML FAtt 21 57 0 25 Feb 2021
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Counterfactual Generation for Chest X-rays Joseph Paul Cohen Rupert Brooks Sovann En Evan Zucker Anuj Pareek M. Lungren Akshay S. Chaudhari FAtt MedIm 29 3 0 18 Feb 2021
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 25 22 0 14 Feb 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 37 169 0 13 Jan 2021
Robust Machine Learning Systems: Challenges, Current Trends, Perspectives, and the Road Ahead Muhammad Shafique Mahum Naseer T. Theocharides C. Kyrkou O. Mutlu Lois Orosa Jungwook Choi OOD 73 100 0 04 Jan 2021
On Baselines for Local Feature Attributions Johannes Haug Stefan Zurn Peter El-Jiz Gjergji Kasneci FAtt 8 31 0 04 Jan 2021
iGOS++: Integrated Gradient Optimized Saliency by Bilateral Perturbations Saeed Khorram T. Lawson Fuxin Li AAML FAtt 11 26 0 31 Dec 2020
Understanding Learned Reward Functions Eric J. Michaud Adam Gleave Stuart J. Russell XAI OffRL 9 33 0 10 Dec 2020
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 16 18 0 10 Dec 2020
Interpretable Graph Capsule Networks for Object Recognition Jindong Gu Volker Tresp FAtt 9 36 0 03 Dec 2020
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski 19 111 0 29 Nov 2020
Reflective-Net: Learning from Explanations Johannes Schneider Michalis Vlachos FAtt OffRL LRM 52 18 0 27 Nov 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 24 241 0 21 Nov 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 11 84 0 12 Nov 2020
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning Iro Laina Ruth C. Fong Andrea Vedaldi OCL 20 13 0 27 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 34 7 0 23 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 28 62 0 20 Oct 2020
Interpretable Machine Learning -- A Brief History, State-of-the-Art and Challenges Christoph Molnar Giuseppe Casalicchio B. Bischl AI4TS AI4CE 10 397 0 19 Oct 2020