Neural networks : the official journal of the International Neural Network Society
Dec 24, 2024
The explainability of Graph Neural Networks (GNNs) is critical to various GNN applications, yet it remains a significant challenge. A convincing explanation should be both necessary and sufficient simultaneously. However, existing GNN explaining appr...
Neural networks : the official journal of the International Neural Network Society
Dec 24, 2024
This paper investigates the probabilistic-sampling-based asynchronous control problem for semi-Markov reaction-diffusion neural networks (SMRDNNs). Aiming at mitigating the drawback of the well-known fixed-sampling control law, a more general probabi...
Neural networks : the official journal of the International Neural Network Society
Dec 20, 2024
Graph Out-of-Distribution (OOD), requiring that models trained on biased data generalize to the unseen test data, has considerable real-world applications. One of the most mainstream methods is to extract the invariant subgraph by aligning the origin...
Fall is a common adverse event among older adults. This study aimed to identify essential fall factors and develop a machine learning-based prediction model to predict the fall risk category among community-dwelling older adults, leading to earlier i...
We address an open problem in the philosophy of artificial intelligence (AI): how to justify the epistemic attitudes we have towards the trustworthiness of AI systems. The problem is important, as providing reasons to believe that AI systems are wort...
Neural networks : the official journal of the International Neural Network Society
Nov 20, 2024
Hyper-parameter optimization (HPO) aims to improve the performance of machine learning algorithms by identifying appropriate hyper-parameters. By converting the computation of expected improvement into density-ratio estimation problems, existing work...
Predicting the probability that a given location will be burnt by a wildfire is an important part of understanding the risk that wildfires pose and how our management actions (e.g., prescribed burning) can reduce this risk. Existing methods to quanti...
Journal of imaging informatics in medicine
Sep 12, 2024
The purpose of this study was to evaluate the impact of probability map threshold on pleural mesothelioma (PM) tumor delineations generated using a convolutional neural network (CNN). One hundred eighty-six CT scans from 48 PM patients were segmented...
Neural networks : the official journal of the International Neural Network Society
Sep 3, 2024
In the real world, the correct recognition of traffic signs plays a crucial role in vehicle autonomous driving and traffic monitoring. The research on its adversarial attack can test the security of vehicle autonomous driving system and provide enlig...
Neural networks : the official journal of the International Neural Network Society
Aug 19, 2024
Neural ordinary differential equations have emerged as a natural tool for supervised learning from a control perspective, yet a complete understanding of the role played by their architecture remains elusive. In this work, we examine the interplay be...
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