UB Paderborn / Katalog / Suche / in CDI

Sortiert nach

Einfacher Volltextzugriff von (fast) überall

Installieren Sie die LibKey Nomad-Browsererweiterung und erhalten Sie von vielen Webseiten einfachen Zugriff auf lizenzierte Volltexte oder Open Access Publikationen. Mehr erfahren...

Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information

IEEE transactions on knowledge and data engineering, 2023-07, Vol.35 (7), p.7103-7117

2023

Volltextzugriff (PDF)

Towards Prototype-Based Self-Explainable Graph Neural Network

ACM transactions on knowledge discovery from data, 2024-08

2024

Volltextzugriff (PDF)

Times series forecasting for urban building energy consumption based on graph convolutional network

Applied energy, 2022-02, Vol.307, p.118231, Article 118231

2022

Volltextzugriff (PDF)

Improving Issue-PR Link Prediction via Knowledge-Aware Heterogeneous Graph Learning

IEEE transactions on software engineering, 2024-07, Vol.50 (7), p.1901-1920

2024

Volltextzugriff (PDF)

Learning fair models without sensitive attributes: A generative approach

Neurocomputing (Amsterdam), 2023-12, Vol.561, p.126841, Article 126841

2023

Volltextzugriff (PDF)

Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information

Proceedings of the 14th ACM International Conference on Web Search and Data Mining, 2021, p.680-688

2021

Volltextzugriff (PDF)

Towards Self-Explainable Graph Neural Network

Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 2021, p.302-311

2021

Volltextzugriff (PDF)

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability

Machine Intelligence Research, 2024-09

2024

Volltextzugriff (PDF)

NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021, p.227-236

2021

Volltextzugriff (PDF)

Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels

Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022, p.181-191

2022

Volltextzugriff (PDF)

Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features

Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining, 2022, p.1433-1442

2022

Volltextzugriff (PDF)

Unnoticeable Backdoor Attacks on Graph Neural Networks

Proceedings of the ACM Web Conference 2023, 2023, p.2263-2273

2023

Volltextzugriff (PDF)

Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024, p.4386-4397

2024

Volltextzugriff (PDF)

HP-GMN: Graph Memory Networks for Heterophilous Graphs

2022 IEEE International Conference on Data Mining (ICDM), 2022, p.1263-1268

2022

Volltextzugriff (PDF)

Unsupervised Image Super-Resolution with an Indirect Supervised Path

2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2020, p.1924-1933

2020

Volltextzugriff (PDF)

A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023, p.368-379

2023

Volltextzugriff (PDF)

Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository

Proceedings of the International AAAI Conference on Web and Social Media, 2020-05, Vol.14, p.853-862

2020

Volltextzugriff (PDF)

Labeled Data Generation with Inexact Supervision

Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021, p.218-226

2021

Volltextzugriff (PDF)

Learning About Explainable AI with Very Little Programming: For 4th\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$4\mbox{th}$$\end{document} Year Undergrads (or Younger)

Innovative Practices in Teaching Information Sciences and Technology, p.121-138

Volltextzugriff (PDF)

Psychological characteristics and GoNogo research of patients with functional constipation

Medicine (Baltimore), 2016-12, Vol.95 (52), p.e5685-e5685

2016

Volltextzugriff (PDF)

1 – 20 von 20

Menü

Weitere Dienste

Einstellungen

Learning Fair Graph Neural Networks With Limited and Private Sensitive Attribute Information

Towards Prototype-Based Self-Explainable Graph Neural Network

Times series forecasting for urban building energy consumption based on graph convolutional network

Improving Issue-PR Link Prediction via Knowledge-Aware Heterogeneous Graph Learning

Learning fair models without sensitive attributes: A generative approach

Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information

Towards Self-Explainable Graph Neural Network

A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability

NRGNN: Learning a Label Noise Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs

Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels

Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features

Unnoticeable Backdoor Attacks on Graph Neural Networks

Rethinking Graph Backdoor Attacks: A Distribution-Preserving Perspective

HP-GMN: Graph Memory Networks for Heterophilous Graphs

Unsupervised Image Super-Resolution with an Indirect Supervised Path

A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy

Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository

Labeled Data Generation with Inexact Supervision

Psychological characteristics and GoNogo research of patients with functional constipation

Suchergebnisse filtern