Mar 17 - 21, 2025, The event finished successfully
Dec 3, 2024, Registration open (closed on Feb 28)
Aug 31, 2024, applications for presentations open
Aug 11, 2024, web page open
The birth of information geometry dates back to the mid-20th century. Starting with the discovery of dual connections inherent in families of probability distributions, it has led to a wide range of applications in science.
In light of the advancements in data science today, the significance of information geometry has once again been acknowledged. The purpose of this international conference is to facilitate the exchange of recent developments in information geometry and to establish its theoretical foundations across related fields. The development of information geometry will be explored through a series of invited lectures by leading researchers working in mathematics, machine learning, statistics and general natural sciences, as well as short talks and poster presentations.
The research meeting will be held from March 18 (Tue) to 21 (Fri), 2025, at Hongo Campus, The University of Tokyo, in Tokyo, Japan. There will be a tutorial course in Japanese on March 17 (Mon).
Application for presentations has been closed on Sep 30.
Registration for the research meeting has been closed on Feb 28. We have sent a confirmation email to all the registrants around March 2.
The current program is as follows. See Programme for details.
Carlos Améndola, Technical University of Berlin
Nihat Ay, Hamburg University of Technology
Marco Cuturi, Apple and ENSAE
Akio Fujiwara, Osaka University
Sosuke Ito, The University of Tokyo
Tetsuya J. Kobayashi, The University of Tokyo
Fumiyasu Komaki, The University of Tokyo
Wuchen Li, University of South Carolina
Andrew McCormack, University of Alberta
Hans-Georg Müller, University of California, Davis
Klaus-Robert Müller, Technical University of Berlin
Hiroshi Nagaoka, University of Electro-Communications
Naomichi Nakajima, Shibaura Institute of Technology
Mahito Sugiyama, National Institute of Informatics
Geoffrey Wolfer, Waseda University
Ting-Kam Leonard Wong, University of Toronto
See Abstracts for abstracts of all presentations.
On Mar 17 (Mon), a tutorial course in Japanese will be held at the Institute of Statistical Mathematics, Tachikawa, Tokyo.
Details will be announced here.
Hideitsu Hino, The Institute of Statistical Mathematics
Shiro Ikeda, The Institute of Statistical Mathematics
Takeru Matsuda, The University of Tokyo and RIKEN
Hiroshi Matsuzoe, Nagoya Institute of Technology
Tomonari Sei, The University of Tokyo - chair
Masayuki Henmi, The Institute of Statistical Mathematics
Fumiyasu Komaki, The University of Tokyo
Michiko Okudo, The University of Tokyo
Keisuke Yano, The Institute of Statistical Mathematics
Akio Fujiwara, Osaka University
Noboru Murata, Waseda University
Aug 11, 2024: web page open
Sep 30, 2024: due date of application for a talk
Nov 30, 2024: decision on acceptance by this date
Dec 3, 2024: registration open
Jan 31, 2025: due date of registration for on-site participants (up to capacity of the venue)
Feb 28, 2025: due date of registration for online participants
Mar 17 (tutorial): The Institute of Statistical Mathematics, Tachikawa, Tokyo, Japan
Mar 18 - 21 (research meeting): Faculty of Engineering Bldg 2, Hongo campus, The University of Tokyo, Hongo, Tokyo, Japan
The Institute of Statistical Mathematics
The University of Tokyo
"Strategic Programs" grant from ROIS (Research Organization of Information and Systems)
The Institute of Statistical Mathematics
Grant-in-Aid for Scientific Research (A) JP22H00510 "Construction of Bayesian prediction theory based on infinite-dimensional statistical models and development of data analysis methods" (Principal Investigator: Fumiyasu Komaki)
Grant-in-Aid for Scientific Research (B) JP23K24909 "Analysis of transfer learning based on information geometry" (Principal Investigator: Hideitsu Hino)
Springer journal Information Geometry will publish a special issue for FDIG2025. All speakers and attendees are encouraged to submit their papers. The papers will be reviewed through the standard peer review process. Further details will be announced at a later date.