AIMC Topic: Neural Networks, Computer

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Generalization analysis of adversarial pairwise learning.

Neural networks : the official journal of the International Neural Network Society
Adversarial pairwise learning has become the predominant method to enhance the discrimination ability of models against adversarial attacks, achieving tremendous success in various application fields. Despite excellent empirical performance, adversar...

Raw photoplethysmogram waveforms versus peak-to-peak intervals for machine learning detection of atrial fibrillation: Does waveform matter?

Computer methods and programs in biomedicine
BACKGROUND: Machine learning-based analysis can accurately detect atrial fibrillation (AF) from photoplethysmograms (PPGs), however the computational requirements for analyzing raw PPG waveforms can be significant. The analysis of PPG-derived peak-to...

Beyond homophily in spatial-temporal traffic flow forecasting.

Neural networks : the official journal of the International Neural Network Society
Traffic flow forecasting is a crucial yet complex task due to the intricate spatial-temporal correlations arising from road interactions. Recent methods model these interactions using message-passing Graph Convolution Networks (GCNs), which work for ...

Tensor ring rank determination using odd-dimensional unfolding.

Neural networks : the official journal of the International Neural Network Society
While tensor ring (TR) decomposition methods have been extensively studied, the determination of TR-ranks remains a challenging problem, with existing methods being typically sensitive to the determination of the starting rank (i.e., the first rank t...

Multi-hop interpretable meta learning for few-shot temporal knowledge graph completion.

Neural networks : the official journal of the International Neural Network Society
Multi-hop path completion is a key part of temporal knowledge graph completion, which aims to infer complex relationships and obtain interpretable completion results. However, the traditional multi-hop path completion models mainly focus on the stati...

Lie group convolution neural networks with scale-rotation equivariance.

Neural networks : the official journal of the International Neural Network Society
The weight-sharing mechanism of convolutional kernels ensures the translation equivariance of convolutional neural networks (CNNs) but not scale and rotation equivariance. This study proposes a SIM(2) Lie group-CNN, which can simultaneously keep scal...

Event-based adaptive fixed-time optimal control for saturated fault-tolerant nonlinear multiagent systems via reinforcement learning algorithm.

Neural networks : the official journal of the International Neural Network Society
This article investigates the problem of adaptive fixed-time optimal consensus tracking control for nonlinear multiagent systems (MASs) affected by actuator faults and input saturation. To achieve optimal control, reinforcement learning (RL) algorith...

Estimating global phase synchronization by quantifying multivariate mutual information and detecting network structure.

Neural networks : the official journal of the International Neural Network Society
In neuroscience, phase synchronization (PS) is a crucial mechanism that facilitates information processing and transmission between different brain regions. Specifically, global phase synchronization (GPS) characterizes the degree of PS among multiva...

Regional PM prediction with hybrid directed graph neural networks and Spatio-temporal fusion of meteorological factors.

Environmental pollution (Barking, Essex : 1987)
Traditional statistical prediction methods on PM often focus on a single temporal or spatial dimension, with limited consideration for regional transport interactions among adjacent cities. To address this limitation, we propose a hybrid directed gra...

Rapid in vivo EPID image prediction using a combination of analytically calculated attenuation and AI predicted scatter.

Medical physics
BACKGROUND: The electronic portal imaging device (EPID) can be used in vivo, to detect on-treatment errors by evaluating radiation exiting a patient. To detect deviations from the planning intent, image predictions need to be modeled based on the pat...