Do Explanations Reflect Decisions? A Machine-centric Strategy to
Quantify the Performance of Explainability Algorithms

Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms

16 October 2019

Michael St. Jules

Papers citing "Do Explanations Reflect Decisions? A Machine-centric Strategy to Quantify the Performance of Explainability Algorithms"

13 / 13 papers shown

Title
Interactive Diabetes Risk Prediction Using Explainable Machine Learning: A Dash-Based Approach with SHAP, LIME, and Comorbidity Insights Udaya Allani FAtt 35 0 0 08 May 2025
An adversarial attack approach for eXplainable AI evaluation on deepfake detection models Balachandar Gowrisankar V. Thing AAML 34 11 0 08 Dec 2023
Can We Trust Explainable AI Methods on ASR? An Evaluation on Phoneme Recognition Xiao-lan Wu P. Bell A. Rajan 19 5 0 29 May 2023
COVID-Net USPro: An Open-Source Explainable Few-Shot Deep Prototypical Network to Monitor and Detect COVID-19 Infection from Point-of-Care Ultrasound Images Jessy Song Ashkan Ebadi A. Florea Pengcheng Xi Stéphane Tremblay Alexander Wong 30 0 0 04 Jan 2023
SolderNet: Towards Trustworthy Visual Inspection of Solder Joints in Electronics Manufacturing Using Explainable Artificial Intelligence Hayden Gunraj P. Guerrier Sheldon Fernandez Alexander Wong 4 8 0 18 Nov 2022
Evaluating Feature Attribution Methods in the Image Domain Arne Gevaert Axel-Jan Rousseau Thijs Becker D. Valkenborg T. D. Bie Yvan Saeys FAtt 21 22 0 22 Feb 2022
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis Thomas Fel Mélanie Ducoffe David Vigouroux Rémi Cadène Mikael Capelle C. Nicodeme Thomas Serre AAML 23 41 0 15 Feb 2022
Topological Representations of Local Explanations Peter Xenopoulos G. Chan Harish Doraiswamy L. G. Nonato Brian Barr Claudio Silva FAtt 20 4 0 06 Jan 2022
COVID-Net US: A Tailored, Highly Efficient, Self-Attention Deep Convolutional Neural Network Design for Detection of COVID-19 Patient Cases from Point-of-care Ultrasound Imaging Alexander MacLean Saad Abbasi Ashkan Ebadi Andy Zhao Maya Pavlova Hayden Gunraj Pengcheng Xi S. Kohli Alexander Wong 15 9 0 05 Aug 2021
COVID-Net CXR-S: Deep Convolutional Neural Network for Severity Assessment of COVID-19 Cases from Chest X-ray Images Hossein Aboutalebi Maya Pavlova M. Shafiee A. Sabri Amer Alaref Alexander Wong 13 31 0 01 May 2021
Fibrosis-Net: A Tailored Deep Convolutional Neural Network Design for Prediction of Pulmonary Fibrosis Progression from Chest CT Images A. Wong Jack Lu Adam Dorfman Paul McInnis M. Famouri Daniel Manary J. Lee Michael Lynch AI4CE 20 18 0 06 Mar 2021
Explainable deep learning models in medical image analysis Amitojdeep Singh S. Sengupta Vasudevan Lakshminarayanan XAI 35 482 0 28 May 2020
Explaining Explanations: Axiomatic Feature Interactions for Deep Networks Joseph D. Janizek Pascal Sturmfels Su-In Lee FAtt 27 143 0 10 Feb 2020