Sanity Checks for Saliency Maps

8 October 2018

Justin Gilmer

Papers citing "Sanity Checks for Saliency Maps"

50 / 357 papers shown

Title
Sanity Simulations for Saliency Methods Joon Sik Kim Gregory Plumb Ameet Talwalkar FAtt 38 17 0 13 May 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks Eric Wong Shibani Santurkar A. Madry FAtt 22 88 0 11 May 2021
Do Feature Attribution Methods Correctly Attribute Features? Yilun Zhou Serena Booth Marco Tulio Ribeiro J. Shah FAtt XAI 33 132 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 31 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 49 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 33 23 0 07 Apr 2021
White Box Methods for Explanations of Convolutional Neural Networks in Image Classification Tasks Meghna P. Ayyar J. Benois-Pineau A. Zemmari FAtt 9 17 0 06 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 16 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 35 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 59 653 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 37 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 28 75 0 18 Mar 2021
Interpretable Machine Learning: Moving From Mythos to Diagnostics Valerie Chen Jeffrey Li Joon Sik Kim Gregory Plumb Ameet Talwalkar 32 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 37 4 0 18 Feb 2021
Connecting Interpretability and Robustness in Decision Trees through Separation Michal Moshkovitz Yao-Yuan Yang Kamalika Chaudhuri 30 22 0 14 Feb 2021
Convolutional Neural Network Interpretability with General Pattern Theory Erico Tjoa Cuntai Guan FAtt AI4CE 16 6 0 05 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 78 100 0 04 Jan 2021
On Baselines for Local Feature Attributions Johannes Haug Stefan Zurn Peter El-Jiz Gjergji Kasneci FAtt 13 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
Towards Robust Explanations for Deep Neural Networks Ann-Kathrin Dombrowski Christopher J. Anders K. Müller Pan Kessel FAtt 21 63 0 18 Dec 2020
Improving 3D convolutional neural network comprehensibility via interactive visualization of relevance maps: Evaluation in Alzheimer's disease M. Dyrba Moritz Hanzig S. Altenstein Sebastian Bader Tommaso Ballarini ... B. Ertl-Wagner M. Wagner J. Wiltfang F. Jessen S. Teipel FAtt MedIm 34 51 0 18 Dec 2020
Understanding Learned Reward Functions Eric J. Michaud Adam Gleave Stuart J. Russell XAI OffRL 22 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 24 18 0 10 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
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 57 18 0 27 Nov 2020
Explaining by Removing: A Unified Framework for Model Explanation Ian Covert Scott M. Lundberg Su-In Lee FAtt 36 241 0 21 Nov 2020
Robust and Stable Black Box Explanations Himabindu Lakkaraju Nino Arsov Osbert Bastani AAML FAtt 24 84 0 12 Nov 2020
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning Iro Laina Ruth C. Fong Andrea Vedaldi OCL 33 13 0 27 Oct 2020
Now You See Me (CME): Concept-based Model Extraction Dmitry Kazhdan B. Dimanov M. Jamnik Pietro Lió Adrian Weller 17 72 0 25 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 39 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 36 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 20 397 0 19 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
Visualizing Color-wise Saliency of Black-Box Image Classification Models Yuhki Hatakeyama Hiroki Sakuma Yoshinori Konishi Kohei Suenaga FAtt 19 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 Deep Neural Networks Oana-Maria Camburu XAI FAtt 28 26 0 04 Oct 2020
Trustworthy Convolutional Neural Networks: A Gradient Penalized-based Approach Nicholas F Halliwell Freddy Lecue FAtt 22 9 0 29 Sep 2020
Instance-based Counterfactual Explanations for Time Series Classification Eoin Delaney Derek Greene Mark T. Keane CML AI4TS 19 89 0 28 Sep 2020