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06/07/2023
Empowering Counterfactual Reasoning over Graph Neural Networks through Inductivity
Graph neural networks (GNNs) have various practical applications, such a...
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06/02/2023
A Survey on Explainability of Graph Neural Networks
Graph neural networks (GNNs) are powerful graph-based deep-learning mode...
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02/11/2023
Differentiable Outlier Detection Enable Robust Deep Multimodal Analysis
Often, deep network models are purely inductive during training and whil...
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10/21/2022
Global Counterfactual Explainer for Graph Neural Networks
Graph neural networks (GNNs) find applications in various domains such a...
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03/15/2022
Incorporating Heterophily into Graph Neural Networks for Graph Classification
Graph neural networks (GNNs) often assume strong homophily in graphs, se...
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01/31/2022
An Exploratory Study of Stock Price Movements from Earnings Calls
Financial market analysis has focused primarily on extracting signals fr...
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12/25/2021
Task and Model Agnostic Adversarial Attack on Graph Neural Networks
Graph neural networks (GNNs) have witnessed significant adoption in the ...
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12/24/2021
A Neural Framework for Learning Subgraph and Graph Similarity Measures
Subgraph similarity search is a fundamental operator in graph analysis. ...
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10/23/2021
Event Detection on Dynamic Graphs
Event detection is a critical task for timely decision-making in graph a...
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12/18/2020
Investigating the Ground-level Ozone Formation and Future Trend in Taiwan
Tropospheric ozone (O3) is an influential ground-level air pollutant whi...
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10/25/2019
Manipulating Node Similarity Measures in Network
Node similarity measures quantify how similar a pair of nodes are in a n...
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03/14/2019
Covert Networks: How Hard is It to Hide?
Covert networks are social networks that often consist of harmful users....
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03/08/2019
Learning Heuristics over Large Graphs via Deep Reinforcement Learning
In this paper, we propose a deep reinforcement learning framework called...
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01/08/2019
