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Scientific Machine Learning and AI for Science Lab
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A lab that approaches physical phenomena through mathematical modeling and machine learning.
AboutAbout the lab
Handling physical phenomena with numerical analysis and machine learning
Professor Takaharu Yaguchi researches mathematical modeling, numerical analysis, machine learning, and geometric mechanics at the Institute of Mathematics for Industry.
Researcher information also lists social network analysis and Morphological Computing as research themes.
Co-authored papers include research on simulating physical phenomena with neural networks designed to respect physical laws such as conservation of energy.
Prof. Yaguchi also holds positions in the Department of Mathematics at the Graduate School of Mathematics and in the Department of Mathematics at the Faculty of Science.
Key terms
- Mathematical modeling
- A method of expressing a phenomenon with mathematical equations and using them to analyze its properties or make predictions.
- Numerical analysis
- A branch of mathematics that deals with methods for approximating solutions to equations and similar problems on a computer.
- Machine learning
- Technology that enables computers to learn rules and patterns from data.
ResearchResearch themes
Researcher information lists social network analysis, machine learning, mathematical modeling, numerical analysis, geometric mechanics, and Morphological Computing as research themes. Co-authored papers include research that designs neural networks to preserve physical laws and applies them to phenomena described by partial differential equations.
View More ↗MembersFaculty
- ProfessorTakaharu Yaguchi
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Report an errorAbout the images
The top and research theme images are illustrative and were not taken at the lab. They are cropped from Wikimedia Commons images. Cropped CC BY-SA images are provided under the same CC BY-SA license as the original (version shown on each line).
- Top image: “FEM Simulation Akustik” Ibsmc / CC BY 4.0 (cropped)
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