Metals are made of randomly oriented crystals at the microscopic-length scale. The alignment of the crystal faces creates an infinite number of configurations and complex patterns, making simulations ...
Background: Biomedical knowledge graphs (KGs), such as the Data Distillery Knowledge Graph (DDKG), capture known relationships among entities (e.g., genes, diseases, proteins), providing valuable ...
Mathematics be a tricky subject, and many students struggle to get the hang of it, finding it difficult to solve problems and equations in class. It requires a special sort of attention that one can’t ...
Modern neural networks, with billions of parameters, are so overparameterized that they can "overfit" even random, structureless data. Yet when trained on datasets with structure, they learn the ...
Graph Neural Networks (GNNs) are reshaping AI by enhancing data interpretation and improving applications. Learn how GNNs are crucial in advancing machine learning models. Graph Neural Networks (GNNs) ...
Abstract: Graph neural networks (GNNs) provide powerful insights into brain neuroimaging technology from the view of graphical networks. However, most existing GNN-based models treat the brain ...
Abstract: Feature representation is a key factor in machine learning-based malware detection, affecting the information expressed and used for detection, the choice of the classifier, and ...
In modern drug discovery, generative molecular design models have greatly expanded the chemical space available to researchers, enabling rapid exploration of new compounds. Yet, a major challenge ...
1 Department of Computer Science and Engineering, Kishoreganj University, Kishoreganj, Bangladesh. 2 Department of Electrical and Computer Engineering, North South University, Dhaka, Bangladesh. 3 ...
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