Frank NIELSEN / フランク・ニールセン Sony Computer Science Laboratories Inc, Tokyo (contact) Senior Researcher, Fellow Biography

• Research: Geometric structures of learning, geometric computing for AI and Information Theory with applications.
  
  
• Publications. Some selection:
  • The Many Faces of Information Geometry, AMS Notices, 2022. Watch the video tutorial
  • Approximation and bounding techniques for the Fisher-Rao distances between parametric statistical models, Handbook of Statistics (51), Elsevier, 2024. (arXiv)
  • On f-Divergences Between Cauchy Distributions, IEEE Transactions on Information Theory, 2023. (arXiv)
  • Statistical divergences between densities of truncated exponential families with nested supports: Duo Bregman and duo Jensen divergences , Entropy 2022.
  • On a Generalization of the Jensen–Shannon Divergence and the Jensen–Shannon Centroid, Entropy, 2022.
  • Revisiting Chernoff information with likelihood ratio exponential families, Entropy 2022.
  • On the chi square and higher-order chi distances for approximating f-divergences, IEEE Signal Processing Letters, 2013. (arXiv)
  • Shape retrieval using hierarchical total Bregman soft clustering, IEEE Transactions on Pattern Analysis and Machine Intelligence 2012.
  • The Burbea-Rao and Bhattacharyya centroids, IEEE Transactions on Information Theory, 2011. (arXiv)
  • Hierarchical clustering, chapter 8 of Introduction to HPC with MPI for Data Science, Springer, 2016.
  
  
• Principal interests:

  Information Geometry, pyBregMan library for Bregman Manifolds Distances, divergences, and mutual information Geometric Science of Information (GSI), biannual conference and satellite events Information Theory Visual Computing Parallel computing and HPC: High Performance Computing

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More detailed home page of my projects and research items.