Yoshinobu Kawahara
Yoshinobu Kawahara (Ph.D.)

Members

  • Team leader
    Yoshinobu Kawahara
  • Special postdoctoral researcher
    Kazu Ghalamkari
  • Postdoctoral researcher
    Velmurugan Gandhi
  • Postdoctoral researcher
    Itsushi Sakata
  • Technical staff I
    Yoshiteru Nishimura
  • Visiting scientist
    Keisuke Fujii
  • Visiting scientist
    Yuka Hashimoto
  • Visiting scientist
    Naoya Takeishi
  • Visiting scientist
    Takuya Konishi
  • Part-time worker I
    Jingjing Bai
  • Part-time worker I
    Ryogo Tanaka
  • Part-time worker II
    Yuto Inui
  • Part-time worker II
    Yuta Miyauchi

Introduction

Laboratory's photo

When making predictions based on intelligent information processing such as machine learning, we usually have prior information about structures among variables in data. In our team, we study theories and algorithms for learning with such structural information. Moreover, we conduct applied researches by applying developed algorithms to a variety of scientific and engineering data.

Main Research Field
Computer Science
Research Field
Physics / Engineering
Research Subjects
Machine learning with structural prior information
Development of optimization algorithms for efficient learning
Learning for analysis of spatiotemporal dynamics
Application of developed methods to scientific and engineering data
Laboratory Website URL
https://mls.ist.osaka-u.ac.jp/en/~kawahara/index.html
RIKEN Website URL
http://www.riken.jp/en/research/labs/aip/generic_tech/struct_learn/

Introduction Video

Structured Learning Team (PI: Yoshinobu Kawahara) thumbnails
Show details
Poster(s)

Related posts

posted on September 24, 2024 14:59Information
Event Report:Young Researchers' Association for Machine Learning (YAML) 2024 (September 21-23, 2024)
posted on August 4, 2024 18:36SeminarWorkshop
Workshop on quantum machine learning - mathematical foundations and applications
posted on May 9, 2024 22:55Information
37 papers have been accepted at ICML 2024
posted on April 4, 2024 18:08InterviewInformation
【Publish】"What will AI Generation Learn: Messages from Female Researchers"(March 28, 2024)
posted on September 25, 2023 20:05Information
35 papers were accepted at NeurIPS 2023
posted on June 19, 2023 12:41Seminar
GPT4 Journal Club Series (RIKEN AIP mini workshop)
posted on January 27, 2023 10:01Information
7 papers have been accepted at AISTATS 2023
posted on May 23, 2022 10:51Information
11 papers have been accepted at ICML 2022
posted on December 6, 2021 15:39InformationPressrelease
Learning interaction rules from multi-animal trajectories via augmented behavioral models
posted on October 7, 2021 12:42Seminar
Structured Learning Team Seminar (Talk by Dr. David Ha, Google Brain)
posted on October 8, 2021 16:33Information
17 papers were accepted at NeurIPS 2021
posted on October 1, 2021 11:43Symposium
A symposium on "Next-Generation AI and Fundamental Technologies Based on Nonlinear Dynamics" （September 21, 2021）
posted on February 1, 2021 09:49Seminar
[17th AIP Open Seminar] Talks by Structured Learning Team
posted on January 27, 2021 11:12Information
Five papers were accepted at AAAI-21
posted on December 24, 2020 13:51Award
FUJII Keisuke and KAWAHARA Yoshinobu received Best Paper Award from Japanese Neural Network Society
posted on November 16, 2020 09:42Pressrelease
The heat diffusion equation shows its power in drug discovery for brain diseases
posted on June 14, 2020 12:27Seminar
[Online] Structured Learning Team Seminar (Dr. Matthias Weissenbacher)
posted on May 28, 2020 15:00Information
Papers were accepted at IJCAI-PRICAI 2020
posted on March 18, 2019 18:33Award
Received RIKEN Ohbu Award 2018: Postdoctoral Researcher Ishikawa, Research Scientist Fukunaga, Research Scientist Fujii
posted on September 7, 2018 17:55Information
Twelve papers are accepted at NeurIPS 2018