AI for Science

The Cornerstone of AI4Science: Comprehensive Review of Geometric Graph Neural Networks

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The Cornerstone of AI4Science: Comprehensive Review of Geometric Graph Neural Networks

Introduction Recently, Renmin University of China, in collaboration with Tencent AI Lab, Tsinghua University, Stanford, and other institutions, published a review paper: “A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applications.” This review systematically organizes the relevant literature on geometric graph neural networks based on a brief introduction to theoretical knowledge such … Read more

AI for Science: Redefining Scientific Research Paradigms

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AI for Science: Redefining Scientific Research Paradigms

AI has developed over more than seventy years, with each technological breakthrough opening up new possibilities for humanity. Its deep integration with scientific research will create countless or infinite possibilities. Under public attention, the Nobel Prize in Chemistry, known for its “direct lineage” to the Nobel Prize, was finally announced this October, awarding three chemists … Read more

AI Deep Learning: The New Key to the High-Dimensional Scientific Revolution

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AI Deep Learning: The New Key to the High-Dimensional Scientific Revolution

Deep Learning is a class of machine learning algorithms that primarily learns the inherent patterns and hierarchical representations of sample data, enabling machines to possess analysis and learning capabilities similar to humans. The ultimate goal of deep learning is to allow machines to recognize and interpret various data, such as text, images, and sounds, thereby … Read more