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09/04/2023
On the Robustness of Post-hoc GNN Explainers to Label Noise
Proposed as a solution to the inherent black-box limitations of graph ne...
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08/29/2023
How Faithful are Self-Explainable GNNs?
Self-explainable deep neural networks are a recent class of models that ...
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05/05/2023
Tiny-PPG: A Lightweight Deep Neural Network for Real-Time Detection of Motion Artifacts in Photoplethysmogram Signals on Edge Devices
Photoplethysmogram (PPG) signals are easily contaminated by motion artif...
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02/16/2023
Knowledge-augmented Graph Machine Learning for Drug Discovery: A Survey from Precision to Interpretability
The integration of Artificial Intelligence (AI) into the field of drug d...
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06/27/2022
"Double vaccinated, 5G boosted!": Learning Attitudes towards COVID-19 Vaccination from Social Media
To address the vaccine hesitancy which impairs the efforts of the COVID-...
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05/19/2022
Simplifying Node Classification on Heterophilous Graphs with Compatible Label Propagation
Graph Neural Networks (GNNs) have been predominant for graph learning ta...
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03/21/2022
Unsupervised Heterophilous Network Embedding via r-Ego Network Discrimination
Recently, supervised network embedding (NE) has emerged as a predominant...
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04/09/2021
The Burden of Being a Bridge: Understanding the Role of Multilingual Users during the COVID-19 Pandemic
The outbreak of the COVID-19 pandemic triggers infodemic over online soc...
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12/13/2020
From #Jobsearch to #Mask: Improving COVID-19 Cascade Prediction with Spillover Effects
As the pandemic of social media panic spreads faster than the COVID-19 o...
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10/26/2020
Reinforcement Learning Enhanced Heterogeneous Graph Neural Network
Heterogeneous Information Networks (HINs), involving a diversity of node...
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10/01/2020
Adaptive Multi-grained Graph Neural Networks
Graph Neural Networks (GNNs) have been increasingly deployed in a multit...
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09/08/2020
Hierarchical Message-Passing Graph Neural Networks
Graph Neural Networks (GNNs) have become a promising approach to machine...
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08/12/2020
