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Distill n' Explain: explaining graph neural networks using simple surrogates.

, , , , и . AISTATS, том 206 из Proceedings of Machine Learning Research, стр. 6199-6214. PMLR, (2023)

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Amauri Simioni

Amauri Simioni

Leonardo Souza Menezes

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Vasco Souza

 

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Improving Graph Variational Autoencoders with Multi-Hop Simple Convolutions., , и . ESANN, (2021)Distill n' Explain: explaining graph neural networks using simple surrogates., , , , и . AISTATS, том 206 из Proceedings of Machine Learning Research, стр. 6199-6214. PMLR, (2023)Going beyond persistent homology using persistent homology., , и . CoRR, (2023)Learning Robust Statistics for Simulation-based Inference under Model Misspecification., , , , и . CoRR, (2023)Provably expressive temporal graph networks., , , и . NeurIPS, (2022)In-n-Out: Calibrating Graph Neural Networks for Link Prediction., , , и . CoRR, (2024)Pattern classification based on regional models., , , и . Appl. Soft Comput., (2022)ConveXplainer for Graph Neural Networks., , , и . BRACIS (2), том 13654 из Lecture Notes in Computer Science, стр. 588-600. Springer, (2022)Procedural Generation of Isometric Racetracks Using Chain Code for Racing Games., , , , и . SBGames, стр. 136-143. IEEE, (2021)Minimal Learning Machine: Theoretical Results and Clustering-Based Reference Point Selection., , , , , и . CoRR, (2019)