Neural networks : the official journal of the International Neural Network Society
May 8, 2025
Subgraph federated learning (subgraph-FL) is a distributed machine learning paradigm enabling cross-client collaborative training of graph neural networks (GNNs). However, real-world subgraph-FL scenarios often face subgraph heterogeneity problem, i....
Neural networks : the official journal of the International Neural Network Society
May 5, 2025
Neural networks have become the standard approach for tasks such as computer vision, machine translation and pattern recognition. While they exhibit significant feature representation capabilities, they often lack interpretability. This suggests that...
Neural networks : the official journal of the International Neural Network Society
May 4, 2025
The temporal knowledge graph (TKG) query enables the retrieval of candidate answer lists by addressing questions that involve temporal constraints, regarded as a crucial downstream task in the realm of the temporal knowledge graph. Existing methods p...
Neural networks : the official journal of the International Neural Network Society
Mar 24, 2025
Zeroing neural networks (ZNNs) are commonly used for dynamic matrix equations, but their performance under numerically unstable conditions has not been thoroughly explored, especially in situations involving unequal row-column matrices. The challenge...
Neural networks : the official journal of the International Neural Network Society
Mar 22, 2025
Anomaly detection in the Industrial Internet of Things (IIoT) aims at identifying abnormal sensor signals to ensure industrial production safety. However, most existing models only focus on high accuracy by building a bulky neural network with deep s...
Neural networks : the official journal of the International Neural Network Society
Mar 22, 2025
Existing neural network models to learn Hamiltonian systems, such as SympNets, although accurate in low-dimensions, struggle to learn the correct dynamics for high-dimensional many-body systems. Herein, we introduce Symplectic Graph Neural Networks (...
Neural networks : the official journal of the International Neural Network Society
Mar 21, 2025
Symbolic Regression (SR) methods in tree representations have exhibited commendable outcomes across Genetic Programming (GP) and deep learning search paradigms. Nonetheless, the tree representation of mathematical expressions occasionally embodies re...
Neural networks : the official journal of the International Neural Network Society
Mar 21, 2025
Session-based recommendation systems aim to predict users' next interactions based on short-lived, anonymous sessions, a challenging yet vital task due to the sparsity and dynamic nature of user behavior. Existing Graph Neural Network (GNN)-based met...
Neural networks : the official journal of the International Neural Network Society
Mar 21, 2025
Heatmap-based anatomical landmark detection is still facing two unresolved challenges: (1) inability to accurately evaluate the distribution of heatmap; (2) inability to effectively exploit global spatial structure information. To address the computa...
Neural networks : the official journal of the International Neural Network Society
Mar 21, 2025
Directed graph neural networks (DGNNs) have garnered increasing interest, yet few studies have focused on node-level representation in directed graphs. In this paper, we argue that different nodes rely on neighbor information from different direction...