甘利先生らにより研究が進められた情報幾何学の基礎的な入門用総説 fMRIのconnectivity解析に用いることで非線形性を考慮した確率分布の比較等がrigidに評価できる可能性 但しKernel関数を含むparameterの設定等の問題は未解決 OA #information_geometry #MRI #papers doi.org/10.3390/e22101…

New Episode with Mathematician Peter Woit Link: youtu.be/TTSeqsCgxj8 In this episode, Peter Woit critiques the long-standing theories of unification in physics, arguing that the pursuit of extra dimensions and supersymmetry has failed. Peter introduces a new approach

Book #OTD on which the talk slides below are based on: "Variational Calculus" by JP Bourguignon a great reading! > link.springer.com/book/10.1007/9…

Further Developments of Information Geometry March 17 - 21, 2025, Tokyo > sites.google.com/view/fdig2025/

😲I found a new kind of books, blending popular science with novel genre! The Specter of Atacama: A Trio for the End of Time 2 books in French by Mathematicians Dixmier (100 yo!) and Connes (former PhD student of Dixmier) odilejacob.fr/catalogue/art-… Ps: I have not read them yet…

Last day of a nice workshop held at Ecole des Mines Paris on Geometry-Informed Machine Learning Some slide decks already available! sites.google.com/view/calistawo…

Interesting new book on the history of vector analysis, reviewed by Ernest Davis siam.org/publications/s…

Ending a good coding day... (Migrated & refreshed old codes to new environments for new problems...) Below are small(est) enclosing Bregman balls with coresets in blue and basis in purple circles with geodesics. > sciencedirect.com/science/articl… PDF> franknielsen.github.io/SlidesVideo/BC…

Periodic update posting! Poster of main distances with underlying geometries 👉 Poster PDF: franknielsen.github.io/Divergence/

💡 A generalization of the Jensen-Shannon divergence from the viewpoint of optimization (=variational definition) with applications. doi.org/10.3390/e23040… "On a Variational Definition for the Jensen-Shannon Symmetrization of Distances Based on the Information Radius"

IPAM program “Mathematics of Intelligences” (September 9 and December 13, 2024) with IPAM workshop Theory and Practice of Deep Learning (October 14-18 2024) > ipam.ucla.edu/programs/works…

An excellent book to learn differential geometry without learning Riemannian metrics! So quite a surprise at first, but it is great to learn differential structures: You will learn differential forms, Lie groups, and de Rham cohomology among others. > link.springer.com/book/10.1007/9…