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Neural networks : the official journal of the International Neural Network Society
Dec 28, 2024
Node classification, seeking to predict the categories of unlabeled nodes, is a crucial task in graph learning. One of the most popular methods for node classification is currently Graph Neural Networks (GNNs). However, conventional GNNs assign equal...
Neural networks : the official journal of the International Neural Network Society
Dec 28, 2024
Graph Neural Networks (GNNs) have garnered significant attention for their success in learning the representation of homophilic or heterophilic graphs. However, they cannot generalize well to real-world graphs with different levels of homophily. In r...
Neural networks : the official journal of the International Neural Network Society
Dec 28, 2024
Document-level event causality identification (ECI) aims to detect causal relations in between event mentions in a document. Some recent approaches model diverse connections in between events, such as syntactic dependency and etc., with a graph neura...
Neural networks : the official journal of the International Neural Network Society
Dec 28, 2024
Real-time online optimisation plays a crucial role in high-frequency trading (HFT) strategies. The Markowitz model, as a Nobel Prize-winning framework, is widely used for portfolio management optimisation by framing the problem as a constrained quadr...
Neural networks : the official journal of the International Neural Network Society
Dec 27, 2024
The class imbalance problem is one of the difficult factors affecting the performance of traditional classifiers. The oversampling technique is the most common way to solve the class imbalance problem. They alleviate the performance impact of the cla...
Neural networks : the official journal of the International Neural Network Society
Dec 27, 2024
Even in the absence of external stimuli, the brain is spontaneously active. Indeed, most cortical activity is internally generated by recurrence. Both theoretical and experimental studies suggest that chaotic dynamics characterize this spontaneous ac...
Neural networks : the official journal of the International Neural Network Society
Dec 27, 2024
Over the past decade, the size of neural network models has gradually increased in both breadth and depth, leading to a growing interest in the application of neural network pruning. Unstructured pruning provides fine-grained sparsity and achieves be...
Neural networks : the official journal of the International Neural Network Society
Dec 27, 2024
Emotion recognition via electroencephalogram (EEG) signals holds significant promise across various domains, including the detection of emotions in patients with consciousness disorders, assisting in the diagnosis of depression, and assessing cogniti...
Neural networks : the official journal of the International Neural Network Society
Dec 27, 2024
Certifying robustness against external uncertainties throughout the control process to reduce the risk of instability is very important. Most existing approaches based on adversarial learning use a fixed parameter to adjust the intensity of adversari...
Neural networks : the official journal of the International Neural Network Society
Dec 26, 2024
Limited transferability hinders the performance of a well-trained deep learning model when applied to new application scenarios. Recently, Unsupervised Domain Adaptation (UDA) has achieved significant progress in addressing this issue via learning do...