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Neural networks : the official journal of the International Neural Network Society
Jan 16, 2025
Brain-inspired spiking neural networks (SNNs) are increasingly explored for their potential in spatiotemporal information modeling and energy efficiency on emerging neuromorphic hardware. Recent works incorporate attentional modules into SNNs, greatl...
Neural networks : the official journal of the International Neural Network Society
Jan 16, 2025
Long time series forecasting has extensive applications in various fields such as power dispatching, traffic control, and weather forecasting. Recently, models based on the Transformer architecture have dominated the field of time series forecasting....
Neural networks : the official journal of the International Neural Network Society
Jan 16, 2025
Image steganography, defined as the practice of concealing information within another image. In this paper, we propose decay weight invertible image steganography with private key (DKiS). This model introduces two major advancements into current inve...
Neural networks : the official journal of the International Neural Network Society
Jan 15, 2025
Entity alignment (EA) is a typical strategy for knowledge graph integration, aiming to identify and align different entity pairs representing the same real object from different knowledge graphs. Temporal Knowledge Graph (TKG) extends the static know...
Neural networks : the official journal of the International Neural Network Society
Jan 15, 2025
Artificial Neural Networks (ANNs) aim at mimicking information processing in biological networks. In cognitive neuroscience, graph modeling is a powerful framework widely used to study brain structural and functional connectivity. Yet, the extension ...
Neural networks : the official journal of the International Neural Network Society
Jan 14, 2025
Video anomaly detection plays a crucial role in ensuring public safety. Its goal is to detect abnormal patterns contained in video frames. Most existing models distinguish the anomalies based on the Mean Squared Error (MSE), which is hard to align wi...
Neural networks : the official journal of the International Neural Network Society
Jan 14, 2025
For imbalanced classification problem, algorithm-level methods can effectively avoid the information loss and noise introduction of data-level methods. However, the differences in the characteristics of the datasets, such as imbalance ratio, data dim...
Neural networks : the official journal of the International Neural Network Society
Jan 14, 2025
In partial multi-label learning (PML), each instance is associated with multiple candidate labels, but only a subset is the ground-truth label. Due to the ambiguous label information, PML is more challenging than traditional multi-label learning. Con...
Neural networks : the official journal of the International Neural Network Society
Jan 13, 2025
This paper discusses the nuanced domain of nonlinear feature selection in heterogeneous systems. To address this challenge, we present a sparsity-driven methodology, namely nonlinear feature selection for support vector quantile regression (NFS-SVQR)...
Neural networks : the official journal of the International Neural Network Society
Jan 13, 2025
Federated Learning (FL) is a popular framework for data privacy protection in distributed machine learning. However, current FL faces some several problems and challenges, including the limited amount of client data and data heterogeneity. These lead...