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Neural networks : the official journal of the International Neural Network Society
Jan 13, 2025
Graph neural networks (GNNs) have shown great promise in modeling graph-structured data, but the over-smoothing problem restricts their effectiveness in deep layers. Two key weaknesses of existing research on deep GNN models are: (1) ignoring the ben...
Neural networks : the official journal of the International Neural Network Society
Jan 12, 2025
Lamb waves are widely used for defect detection in structural health monitoring, and various methods are developed for Lamb wave data analysis. This paper presents an unsupervised Adversarial Transformer model for anomalous Lamb wave pattern detectio...
Neural networks : the official journal of the International Neural Network Society
Jan 11, 2025
Integrating visual features has been proven effective for deep learning-based speech quality enhancement, particularly in highly noisy environments. However, these models may suffer from redundant information, resulting in performance deterioration w...
Neural networks : the official journal of the International Neural Network Society
Jan 10, 2025
Artificial neural networks (ANNs) can help camera-based remote photoplethysmography (rPPG) in measuring cardiac activity and physiological signals from facial videos, such as pulse wave, heart rate and respiration rate with better accuracy. However, ...
Neural networks : the official journal of the International Neural Network Society
Jan 9, 2025
Sequential Recommendation is based on modelling sequential dependencies in user interactions to produce subsequent recommendation results. However, due to the diversity of users' interests and the uncertainty of their behaviours, not all historical i...
Neural networks : the official journal of the International Neural Network Society
Jan 9, 2025
Active learning on graphs (ALG) has emerged as a compelling research field due to its capacity to address the challenge of label scarcity. Existing ALG methods incorporate diversity into their query strategies to maximize the gains from node sampling...
Neural networks : the official journal of the International Neural Network Society
Jan 9, 2025
Graph Neural Networks (GNNs) have received extensive research attention due to their powerful information aggregation capabilities. Despite the success of GNNs, most of them suffer from the popularity bias issue in a graph caused by a small number of...
Neural networks : the official journal of the International Neural Network Society
Jan 8, 2025
Attention mechanisms have revolutionized natural language processing. Combining them with quantum computing aims to further advance this technology. This paper introduces a novel Quantum Mixed-State Self-Attention Network (QMSAN) for natural language...
Neural networks : the official journal of the International Neural Network Society
Jan 8, 2025
By dynamic planning, we refer to the ability of the human brain to infer and impose motor trajectories related to cognitive decisions. A recent paradigm, active inference, brings fundamental insights into the adaptation of biological organisms, const...
Neural networks : the official journal of the International Neural Network Society
Jan 8, 2025
Conditional adversarial domain adaptation (CADA) is one of the most commonly used unsupervised domain adaptation (UDA) methods. CADA introduces multimodal information to the adversarial learning process to align the distributions of the labeled sourc...