research
∙
06/14/2023
A Unified Framework of Graph Information Bottleneck for Robustness and Membership Privacy
Graph Neural Networks (GNNs) have achieved great success in modeling gra...
share
research
∙
02/11/2023
Unnoticeable Backdoor Attacks on Graph Neural Networks
Graph Neural Networks (GNNs) have achieved promising results in various ...
research
∙
10/05/2022
Towards Prototype-Based Self-Explainable Graph Neural Network
Graph Neural Networks (GNNs) have shown great ability in modeling graph-...
research
∙
04/18/2022
A Comprehensive Survey on Trustworthy Graph Neural Networks: Privacy, Robustness, Fairness, and Explainability
Graph Neural Networks (GNNs) have made rapid developments in the recent ...
research
∙
02/16/2022
Graph-Augmented Normalizing Flows for Anomaly Detection of Multiple Time Series
Anomaly detection is a widely studied task for a broad variety of data t...
research
∙
01/01/2022
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels
Graph Neural Networks (GNNs) have shown their great ability in modeling ...
research
∙
10/15/2021
Label-Wise Message Passing Graph Neural Network on Heterophilic Graphs
Graph Neural Networks (GNNs) have achieved remarkable performance in mod...
research
∙
08/26/2021
Towards Self-Explainable Graph Neural Network
Graph Neural Networks (GNNs), which generalize the deep neural networks ...
research
∙
06/08/2021
Labeled Data Generation with Inexact Supervision
The recent advanced deep learning techniques have shown the promising re...
research
∙
06/08/2021
NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs
Graph Neural Networks (GNNs) have achieved promising results for semi-su...
research
∙
05/27/2021
Times Series Forecasting for Urban Building Energy Consumption Based on Graph Convolutional Network
The world is increasingly urbanizing and the building industry accounts ...
research
∙
04/29/2021
You Can Still Achieve Fairness Without Sensitive Attributes: Exploring Biases in Non-Sensitive Features
Though machine learning models are achieving great success, ex-tensive s...
research
∙
09/29/2020
TEST_POSITIVE at W-NUT 2020 Shared Task-3: Joint Event Multi-task Learning for Slot Filling in Noisy Text
The competition of extracting COVID-19 events from Twitter is to develop...
research
∙
09/03/2020
FairGNN: Eliminating the Discrimination in Graph Neural Networks with Limited Sensitive Attribute Information
Graph neural networks (GNNs) have shown great power in modeling graph st...
research
∙
01/27/2020
Ginger Cannot Cure Cancer: Battling Fake Health News with a Comprehensive Data Repository
Nowadays, Internet is a primary source of attaining health information. ...
research
∙
10/07/2019