Deep Learning and physics 2019
Target scope of Conference

Deep learning plays a central role in recent developments in research in artificial intelligence (AI). Various ideas based on physics are found in the research of deep learning, and consequently, deep learning and physics are related intimately. This international conference is dedicated to (1) applications of deep learning to physics, (2) discovering similarities among deep learning and physics, and (3) leading to new paradigm in physics motivated by deep learning. Researchers in related fields are welcome to attending discussions at the conference.

Organizers

Koji Hashimoto (Osaka U), Masatoshi Imada (Toyota RIKEN / Waseda U), Kouji Kashiwa (Fukuoka Institute of Technology), Yuki Nagai (JAEA), Masayuki Ohzeki (Tohoku U), Enrico Rinaldi (Riken & Arithmer Inc.), Akinori Tanaka (RIKEN AIP), Akio Tomiya (Riken BNL)

Date and Place

31 Oct - 2 Nov 2019

Panasonic Auditorium, Yukawa Hall, Yukawa institute for theoretical physics, Kyoto university

Invited speakers

Shun-Ichi Amari (RIKEN)
Hong-Ye Hu (UC San Diego)
Gurtej Kanwar (MIT)
Sven Krippendorf (Arnold Sommerfeld Center)
Junwei Liu (Hong Kong Univ. Sci. Tech.)
Zi Yang Meng (Chinese Academy of Sciences)
Youichiro Miyake (Square Enix)
Masayuki Ohzeki (Tohoku Univ.)
Fabian Ruhle (CERN)
Rak-Kyeong Seong (Samsung SDS)
Gary Shiu (Univ. Wisconsin)
Lei Wang (Chinese Academy of Sciences)
Youhei Yamaji (Tokyo Univ.)
Greg Yang (Microsoft Research)
Hajime Yoshino (Osaka Univ.)
James Halverson (Northeastern Univ.) : Special lecture at Osaka Univ. on 30 October 2019

Schedule

Coming soon


Registration

Click here for the registration form


In case the number of registered participants exceeds a limit of the capacity of the venue, we may close the registration earlier.
Poster presentation

We will have a poster session at the conference. Please apply at the registration link above.

Access

Access to the workshop site

Poster

Poster

Links to past conferences and related conferences

Deep Learning and physics (Osaka Univ.)

Deep Learning and physics 2018 (Osaka Univ.)

Tsinghua Workshop on Machine Learning in Geometry and Physics 2018 (Tsinghua Sanya International Mathematics Forum)

Physics ∩ ML (Microsoft Research)

Contact

email

Sponsors

本研究会は新学術領域科研費「次世代物質探索のための離散幾何学」との共催です。
また、 以下の研究費にサポートを受けて開催されます:科研費17H06462、科研費18K13548、 ポスト「京」プロジェクト「世代の産業を支える新機能デバイス・高性能材料の創成」