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Recovering Riemannian Metric Distance from Random Geometric Graphs

Han HuangMIT

Research Scientist

50:26·2026·research level·Research Seminar

An investigation into the challenging problem of accurately recovering Riemannian metric distance properties solely from the structure of random geometric graphs.

MathematicsEngineeringComplex Systems & Scalingrandom graphsRiemannian geometrymetric spaces
Source: Simons Institute for the Theory of Computing via YouTubeWatch on YouTube
LecturerAll lecturers →
Han Huang

Research Scientist

1 lectureCanon

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