Sanity Checks for Saliency Maps

8 October 2018

Justin Gilmer

Papers citing "Sanity Checks for Saliency Maps"

50 / 357 papers shown

Title
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective Xiwei Xuan Ziquan Deng Hsuan-Tien Lin Z. Kong Kwan-Liu Ma AAML FAtt 35 2 0 01 Mar 2023
Don't be fooled: label leakage in explanation methods and the importance of their quantitative evaluation N. Jethani A. Saporta Rajesh Ranganath FAtt 29 10 0 24 Feb 2023
The Generalizability of Explanations Hanxiao Tan FAtt 18 1 0 23 Feb 2023
sMRI-PatchNet: A novel explainable patch-based deep learning network for Alzheimer's disease diagnosis and discriminative atrophy localisation with Structural MRI Xin Zhang Liangxiu Han Lianghao Han Haoming Chen Darren Dancey Daoqiang Zhang MedIm 18 4 0 17 Feb 2023
Less is More: The Influence of Pruning on the Explainability of CNNs David Weber F. Merkle Pascal Schöttle Stephan Schlögl Martin Nocker FAtt 34 1 0 17 Feb 2023
The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus Anna Hedström P. Bommer Kristoffer K. Wickstrom Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne 37 21 0 14 Feb 2023
On The Coherence of Quantitative Evaluation of Visual Explanations Benjamin Vandersmissen José Oramas XAI FAtt 34 3 0 14 Feb 2023
Human-Centric Multimodal Machine Learning: Recent Advances and Testbed on AI-based Recruitment Alejandro Peña Ignacio Serna Aythami Morales Julian Fierrez Alfonso Ortega Ainhoa Herrarte Manuel Alcántara J. Ortega-Garcia FaML 25 34 0 13 Feb 2023
A novel approach to generate datasets with XAI ground truth to evaluate image models Miquel Miró-Nicolau Antoni Jaume-i-Capó Gabriel Moyà Alcover 22 4 0 11 Feb 2023
Understanding User Preferences in Explainable Artificial Intelligence: A Survey and a Mapping Function Proposal M. Hashemi Ali Darejeh Francisco Cruz 40 3 0 07 Feb 2023
Variational Information Pursuit for Interpretable Predictions Aditya Chattopadhyay Kwan Ho Ryan Chan B. Haeffele D. Geman René Vidal DRL 21 10 0 06 Feb 2023
Stop overkilling simple tasks with black-box models and use transparent models instead Matteo Rizzo Matteo Marcuzzo A. Zangari A. Gasparetto A. Albarelli VLM 21 0 0 06 Feb 2023
ProtoSeg: Interpretable Semantic Segmentation with Prototypical Parts Mikolaj Sacha Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski VLM 35 29 0 28 Jan 2023
Holistically Explainable Vision Transformers Moritz D Boehle Mario Fritz Bernt Schiele ViT 35 9 0 20 Jan 2023
TAME: Attention Mechanism Based Feature Fusion for Generating Explanation Maps of Convolutional Neural Networks Mariano V. Ntrougkas Nikolaos Gkalelis Vasileios Mezaris FAtt 19 8 0 18 Jan 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 36 22 0 17 Jan 2023
Towards Reconciling Usability and Usefulness of Explainable AI Methodologies Pradyumna Tambwekar Matthew C. Gombolay 28 8 0 13 Jan 2023
Saliency-Augmented Memory Completion for Continual Learning Guangji Bai Chen Ling Yuyang Gao Liang Zhao CLL 40 4 0 26 Dec 2022
Impossibility Theorems for Feature Attribution Blair Bilodeau Natasha Jaques Pang Wei Koh Been Kim FAtt 20 68 0 22 Dec 2022
Counterfactual Explanations for Misclassified Images: How Human and Machine Explanations Differ Eoin Delaney A. Pakrashi Derek Greene Markt. Keane 35 15 0 16 Dec 2022
Robust Explanation Constraints for Neural Networks Matthew Wicker Juyeon Heo Luca Costabello Adrian Weller FAtt 26 18 0 16 Dec 2022
Interpretable ML for Imbalanced Data Damien Dablain C. Bellinger Bartosz Krawczyk D. Aha Nitesh V. Chawla 24 1 0 15 Dec 2022
On the Relationship Between Explanation and Prediction: A Causal View Amir-Hossein Karimi Krikamol Muandet Simon Kornblith Bernhard Schölkopf Been Kim FAtt CML 31 14 0 13 Dec 2022
Comparing the Decision-Making Mechanisms by Transformers and CNNs via Explanation Methods Ming-Xiu Jiang Saeed Khorram Li Fuxin FAtt 22 9 0 13 Dec 2022
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning Yuyang Gao Siyi Gu Junji Jiang S. Hong Dazhou Yu Liang Zhao 29 39 0 07 Dec 2022
This changes to that : Combining causal and non-causal explanations to generate disease progression in capsule endoscopy Anuja Vats A. Mohammed Marius Pedersen Nirmalie Wiratunga MedIm 29 9 0 05 Dec 2022
Understanding and Enhancing Robustness of Concept-based Models Sanchit Sinha Mengdi Huai Jianhui Sun Aidong Zhang AAML 28 18 0 29 Nov 2022
Towards More Robust Interpretation via Local Gradient Alignment Sunghwan Joo Seokhyeon Jeong Juyeon Heo Adrian Weller Taesup Moon FAtt 30 5 0 29 Nov 2022
Interactive Visual Feature Search Devon Ulrich Ruth C. Fong FAtt 23 0 0 28 Nov 2022
Attribution-based XAI Methods in Computer Vision: A Review Kumar Abhishek Deeksha Kamath 27 18 0 27 Nov 2022
MEGAN: Multi-Explanation Graph Attention Network Jonas Teufel Luca Torresi Patrick Reiser Pascal Friederich 26 8 0 23 Nov 2022
ModelDiff: A Framework for Comparing Learning Algorithms Harshay Shah Sung Min Park Andrew Ilyas A. Madry SyDa 51 26 0 22 Nov 2022
Do graph neural networks learn traditional jet substructure? Farouk Mokhtar Raghav Kansal Javier Mauricio Duarte GNN 34 11 0 17 Nov 2022
Data-Centric Debugging: mitigating model failures via targeted data collection Sahil Singla Atoosa Malemir Chegini Mazda Moayeri Soheil Feiz 24 4 0 17 Nov 2022
CRAFT: Concept Recursive Activation FacTorization for Explainability Thomas Fel Agustin Picard Louis Bethune Thibaut Boissin David Vigouroux Julien Colin Rémi Cadène Thomas Serre 19 102 0 17 Nov 2022
Interpretable Few-shot Learning with Online Attribute Selection M. Zarei Majid Komeili FAtt 35 1 0 16 Nov 2022
What Makes a Good Explanation?: A Harmonized View of Properties of Explanations Zixi Chen Varshini Subhash Marton Havasi Weiwei Pan Finale Doshi-Velez XAI FAtt 33 18 0 10 Nov 2022
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
ViT-CX: Causal Explanation of Vision Transformers Weiyan Xie Xiao-hui Li Caleb Chen Cao Nevin L.Zhang ViT 29 17 0 06 Nov 2022
BOREx: Bayesian-Optimization--Based Refinement of Saliency Map for Image- and Video-Classification Models Atsushi Kikuchi Kotaro Uchida Masaki Waga Kohei Suenaga FAtt 26 1 0 31 Oct 2022
Learning on the Job: Self-Rewarding Offline-to-Online Finetuning for Industrial Insertion of Novel Connectors from Vision Ashvin Nair Brian Zhu Gokul Narayanan Eugen Solowjow Sergey Levine OffRL OnRL 28 14 0 27 Oct 2022
Logic-Based Explainability in Machine Learning Sasha Rubin LRM XAI 47 39 0 24 Oct 2022
Hierarchical Neyman-Pearson Classification for Prioritizing Severe Disease Categories in COVID-19 Patient Data Lijia Wang Y. X. R. Wang Jingyi Jessica Li Xin Tong 21 1 0 01 Oct 2022
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations Grégoire Mialon Randall Balestriero Yann LeCun 32 9 0 29 Sep 2022
Formal Conceptual Views in Neural Networks Johannes Hirth Tom Hanika 15 2 0 27 Sep 2022
Greybox XAI: a Neural-Symbolic learning framework to produce interpretable predictions for image classification Adrien Bennetot Gianni Franchi Javier Del Ser Raja Chatila Natalia Díaz Rodríguez AAML 32 29 0 26 Sep 2022
Ablation Path Saliency Justus Sagemüller Olivier Verdier FAtt AAML 11 0 0 26 Sep 2022
I-SPLIT: Deep Network Interpretability for Split Computing Federico Cunico Luigi Capogrosso Francesco Setti D. Carra Franco Fummi Marco Cristani 29 14 0 23 Sep 2022
Learning Visual Explanations for DCNN-Based Image Classifiers Using an Attention Mechanism Ioanna Gkartzonika Nikolaos Gkalelis Vasileios Mezaris 30 9 0 22 Sep 2022
XClusters: Explainability-first Clustering Hyunseung Hwang Steven Euijong Whang 30 5 0 22 Sep 2022