As an emerging technology in the field of artificial intelligence (AI), graph neural networks (GNNs) are deep learning models designed to process graph-structured data. Currently, GNNs are effective ...
Dr. James McCaffrey presents a complete end-to-end demonstration of linear regression with pseudo-inverse training implemented using JavaScript. Compared to other training techniques, such as ...
SMi Group reports: Alina Alexeenko of Purdue University presenting LyoHub's overview and strategies for the future of lyophilization and alternatives to conventional methods Optimization of ...
Discover how the Modified Dietz Method measures investment returns, factoring in cash flow timing and excluding skewing ...
Abstract: This paper studies the distributed minimax optimization problem over networks. To enhance convergence performance, we propose a distributed optimistic gradient tracking method, termed DOGT, ...
Abstract: Terrain analysis is crucial for the practical application of ground mobile robots in real-world tasks, especially in outdoor unstructured environments. In this article, we use Sparse ...
IOD distinguishes itself as scientific home for researchers working at the boundaries of traditional academic spheres, and generating growing programs in the integration of research with informatics ...
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