AIMC Topic: Neural Networks, Computer

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Mathematical expression exploration with graph representation and generative graph neural network.

Neural networks : the official journal of the International Neural Network Society Jul 1, 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...
Deep Learning Graph Neural Networks Humans Algorithms Neural Networks, Computer
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Motif and supernode-enhanced gated graph neural networks for session-based recommendation.

Neural networks : the official journal of the International Neural Network Society Jul 1, 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...
Algorithms Humans Graph Neural Networks Neural Networks, Computer
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Central loss guides coordinated Transformer for reliable anatomical landmark detection.

Neural networks : the official journal of the International Neural Network Society Jul 1, 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...
Algorithms Anatomic Landmarks Neural Networks, Computer Humans
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A lightweight All-MLP time-frequency anomaly detection for IIoT time series.

Neural networks : the official journal of the International Neural Network Society Jul 1, 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...
Internet of Things Algorithms Time Factors Neural Networks, Computer
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Noise-resistant predefined-time convergent ZNN models for dynamic least squares and multi-agent systems.

Neural networks : the official journal of the International Neural Network Society Jul 1, 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, Computer Least-Squares Analysis Computer Simulation Time Factors Algorithms
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A neural approach to the Turing Test: The role of emotions.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
As is well known, the Turing Test proposes the possibility of distinguishing the behavior of a machine from that of a human being through an experimental session. The Turing Test assesses whether a person asking questions to two different entities, c...
Emotions Electroencephalography Male Cognition Adult Artificial Intelligence Neural Networks, Computer Young Adult Female Humans
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SympGNNs: Symplectic Graph Neural Networks for identifying high-dimensional Hamiltonian systems and node classification.

Neural networks : the official journal of the International Neural Network Society Jul 1, 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 (...
Computer Simulation Molecular Dynamics Simulation Algorithms Graph Neural Networks Neural Networks, Computer
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A novel deep transfer learning method based on explainable feature extraction and domain reconstruction.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Although deep transfer learning has made significant progress, its "black-box" nature and unstable feature adaptation remain key obstacles. This study proposes a multi-stage deep transfer learning method, called XDTL, which combines explainable featu...
Neural Networks, Computer Algorithms Humans Transfer, Psychology Deep Learning
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Adaptive node-level weighted learning for directed graph neural network.

Neural networks : the official journal of the International Neural Network Society Jul 1, 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...
Machine Learning Graph Neural Networks Neural Networks, Computer Learning Algorithms Humans
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Deformation-invariant neural network and its applications in distorted image restoration and analysis.

Neural networks : the official journal of the International Neural Network Society Jul 1, 2025
Images degraded by geometric distortions pose a significant challenge to imaging and computer vision tasks such as object recognition. Deep learning-based imaging models usually fail to give accurate performance for geometrically distorted images. In...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Deep Learning Algorithms Pattern Recognition, Automated
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