Co-hosted by  Osaka CTSR  RIKEN iTHES/iTHEMS Kavli IPMU 

No need of registration for participating.

We are happy to announce our 3rd joint symposium of Osaka CTSR, RIKEN iTHES/iTHEMS and Kavli IPMU, focusing this time on the topic of deep learning and its relation to fundamental physics. The rapid and vast applications of deep learning and artificial intelligence can potentially provide a breakthrough in various situations in fundamental physics. Invited speakers will deliver a cutting-edge progress in this interesting and developing fields, and participants are expected to join discussions.

The symposium  schedule: 

  13:00-13:45 M. Taki (RIKEN)  “Deep Learning : status report

  13:45-14:30 S. Amari (RIKEN) “Statistical Neurodynamics of Deep Networks”

  15:15-15:45 T. Ohtsuki (Sophia U.) “Deep Learning Topological Phases of Random Systems”

  15:45-16:15 A. Tanaka (RIKEN) “Detection of Phase Transition via Convolutional Neural Network”

  16:30-17:00 S. Ikeda (ISM/ Kavli IPMU) “Data Scientific Approach for Astronomy”

  17:00-17:30 N. Suzuki (Kavli IPMU) “Probing Deep Space with Subaru and Hubble Telescope :

                                          Unlocking the Mysteries of Dark Energy and Accelerating Universe”

  17:30-18:00 Y. Kawahara (Osaka U. / RIKEN) “Data-driven modeling of dynamical systems

Closing: 18:00

In addition, in the morning (9:00-12:00) at Nambu hall, we have an informal lecture course on deep learning by M. Taki (in Japanese). 同日午前中(9時から12時まで)には、瀧氏による入門講義「機械学習と深層学習への入門」が南部陽一郎ホールで開催されます。

The venue is Nambu Hall which was newly installed in Osaka university. More information on the venue is found at

The second joint workshop is found at

The first joint symposium  is found at