Global Concept Explanations for Graphs by Contrastive Learning

25 April 2024

Papers citing "Global Concept Explanations for Graphs by Contrastive Learning"

5 / 5 papers shown

Title
Improving Counterfactual Truthfulness for Molecular Property Prediction through Uncertainty Quantification Jonas Teufel Annika Leinweber Pascal Friederich 44 0 0 03 Apr 2025
Sparks of Artificial General Intelligence: Early experiments with GPT-4 Sébastien Bubeck Varun Chandrasekaran Ronen Eldan J. Gehrke Eric Horvitz ... Scott M. Lundberg Harsha Nori Hamid Palangi Marco Tulio Ribeiro Yi Zhang ELM AI4MH AI4CE ALM 212 2,232 0 22 Mar 2023
CF-GNNExplainer: Counterfactual Explanations for Graph Neural Networks Ana Lucic Maartje ter Hoeve Gabriele Tolomei Maarten de Rijke Fabrizio Silvestri 110 142 0 05 Feb 2021
Explainability in Graph Neural Networks: A Taxonomic Survey Hao Yuan Haiyang Yu Shurui Gui Shuiwang Ji 162 589 0 31 Dec 2020
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,658 0 28 Feb 2017