In an era driven by complex data, scientists are increasingly encountering information that doesn't lie neatly on flat, Euclidean surfaces. From 3D medical scans to robot orientations and AI ...
Geometric statistics extends classical statistical methods to data that reside on curved spaces rather than flat Euclidean domains. At its core lies the notion of a manifold: a smooth, curved surface ...
The newly developed Huber mean provides a more stable and reliable way to compute averages for data lying on curved geometric spaces, or Riemannian manifolds. By combining the strengths of ...
Debates over how geometry is understood and learned date back at least to the days of Plato, with more recent scholars concluding that only humans possess the foundations of this understanding.
The analysis of large and complex data sets is one of the most important problems facing the scientific community, and physics in particular. One response to this challenge has been the development of ...
Headed by Professor John Moriarty and Dr Amaranta Membrillo Solis of Queen Mary’s School of Mathematical Sciences, along with collaborators from the University of Nottingham, UCL and École Normale ...
The Norwegian Academy of Science and Letters has awarded the Abel Prize for 2019 to Karen Uhlenbeck, a visiting senior research scholar in mathematics at Princeton, “for her pioneering achievements in ...
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