World models are fast becoming popular to aid in further training of generative AI and large language models (LLMs). Doing so ...

With AI advancements being made faster and faster, it's time to rethink AI governance to safeguard your AI initiatives ...

School of Polymer Science and Polymer Engineering, The University of Akron, Akron, Ohio 44325 United States ...

Here, we showcase how our graph neural network (GNN)-based implicit solvent (GNNIS ... Taxonomy and describe the scientific concepts and themes of the article. Three models with different random seeds ...

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Abstract: Adaptive filtering faces significant challenges in handling complex non-Gaussian noise, while graph signal processing (GSP) excels at processing data with intricate structures. This brief ...

Nonetheless, it often overlooks the issue of data heterogeneity across sites. We propose a Federated Graph Learning-based Cross-Network Layer Feature Alignment (FGLFA) model for MDD identification.