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Shing-Tung Yau on Muck Rack

Shing-Tung Yau

As seen in: The New York Times, Nature, Wiley Online Library, New Scientist, PNAS, Aeon, Astronomy Magazine, Forward, QOSHE
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Articles

Multi-task learning of complex networks via nonlinear ordinary differential equations

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By Ang Dong, Zhifan Li, Shing-Tung Yau, Rongling Wu, Changjian Fa
| Nature Verified
Abstract Complex systems are characterized by many underlying entities and their intricate interactions. We contextualize ecological niche theory and evolutionary game theory through a system of nonlinear mixed ordinary differential equations (nMODEs) to reconstruct informative, dynamic, omnidirectional, and personalized networks (idopNetworks) for complex systems at any dimension.
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An end-to-end generalizable deep learning framework to comprehensively analyze transcriptional regulation

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By Zhaoxi Zhang, Xiaoya Fan, Jiaxin Zhong, Lijuan Jia, Yuanyuan Han, Chenyi Yang, Zengyou He, Xiaoyan Li, Shing-Tung Yau, Rongling Wu, Charles G Danko, Zhong Lin Wang
| Nature Verified
Abstract Genome annotation currently requires performing dozens of molecular assays in hundreds of cell and tissue samples, an expensive endeavor which is impractical to replicate across all species and conditions of interest.
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Mathematics > Differential Geometry

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By Xiaokui Yang, Shing-Tung Yau
| arxiv.org
[Submitted on 11 Mar 2026 (v1), last revised 13 Mar 2026 (this version, v2)] View PDF HTML (experimental) Subjects: Differential Geometry (math.DG) MSC classes: 53C55 Cite as: arXiv:2603.10611 [math.DG] (or arXiv:2603.10611v2 [math.DG] for this version) https://doi.org/10.48550/arXiv.2603.10611
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