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Outputs (8)

MONEY: Ensemble learning for stock price movement prediction via a convolutional network with adversarial hypergraph model (2023)
Journal Article
Sun, Z., Harit, A., Cristea, A. I., Wang, J., & Lio, P. (2023). MONEY: Ensemble learning for stock price movement prediction via a convolutional network with adversarial hypergraph model. AI open, 4, 165-174. https://doi.org/10.1016/j.aiopen.2023.10.002

Stock price prediction is challenging in financial investment, with the AI boom leading to increased interest from researchers. Despite these recent advances, many studies are limited to capturing the time series characteristics of price movement via... Read More about MONEY: Ensemble learning for stock price movement prediction via a convolutional network with adversarial hypergraph model.

Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification (2022)
Presentation / Conference Contribution

Graph neural networks (GNNs) have attracted extensive interest in text classification tasks due to their expected superior performance in representation learning. However, most existing studies adopted the same semi-supervised learning setting as the... Read More about Contrastive Learning with Heterogeneous Graph Attention Networks on Short Text Classification.

A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data (2021)
Presentation / Conference Contribution

This research focuses on semi-supervised classification tasks, specifically for graph-structured data under datascarce situations. It is known that the performance of conventional supervised graph convolutional models is mediocre at classification ta... Read More about A Generative Bayesian Graph Attention Network for Semi-supervised Classification on Scarce Data.