
I investigate the geometric science of information with applications ranging from machine learning to data science, visual computing, and artificial intelligence.
I deal with large high-dimensional, noisy, and heterogeneous dynamic datasets that are inherently non-Euclidean in nature.
To build advanced models and learning machines that capture both regularities and variations of datasets,
I develop geometric computational methods and toolboxes.
Since 2013, I co-organize the biannual international conference "Geometric Science of Information" (GSI).
Worldviews
Keywords
Selected Publications
Nielsen, Frank and Bhatia, Rajendra
Matrix Information Geometrypages , 09, 2013
Nielsen, Frank
K-MLE: A fast algorithm for learning statistical mixture modelsAcoustics, Speech, and Signal Processing, 1988. ICASSP-88., 1988 International Conference on | 03, 2012
Frank Nielsen
Visual Computing: Geometry, Graphics, and VisionJuly, 2005
News & Articles
Fast Proxy Centers for the Jeffreys Centroid: The Jeffreys–Fisher–Rao Center and the Gauss–Bregman Inductive Center
Approximation and bounding techniques for the Fisher-Rao distances
Beyond existing theories, into a new world ~the world of information geometry~