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Tsubaki Masashi  椿 真史

ORCIDConnect your ORCID iD *help
… Alternative Names

椿 真史  ツバキ マサシ

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Researcher Number 80803874
Affiliation (Current) 2022: 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 研究員
Affiliation (based on the past Project Information) *help 2020 – 2022: 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 研究員
2017 – 2018: 国立研究開発法人産業技術総合研究所, 情報・人間工学領域, 研究員
Review Section/Research Field
Principal Investigator
Life / Health / Medical informatics / Basic Section 61030:Intelligent informatics-related
Except Principal Investigator
Basic Section 33020:Synthetic organic chemistry-related / Transformative Research Areas, Section (II)
Keywords
Principal Investigator
深層学習 / 機械学習 / 創薬 / 人工知能 / 密度汎関数理論 / 転移学習 / 量子化学計算 / 密度汎関数法 / データ駆動科学 / マテリアルズ・インフォマティクス / 第一原理計算 … More
Except Principal Investigator
… More 機械学習 / 有機合成 / 転移学習 / 触媒 / 触媒反応 / 収率予測 / 逆解析 / 触媒設計 / 予測モデル Less
  • Research Projects

    (4 results)
  • Research Products

    (18 results)
  • Co-Researchers

    (4 People)
  •  Development of automated catalyst design methodology based on inversed analysis of predictive model

    • Principal Investigator
      矢田 陽
    • Project Period (FY)
      2021 – 2025
    • Research Category
      Grant-in-Aid for Transformative Research Areas (A)
    • Review Section
      Transformative Research Areas, Section (II)
    • Research Institution
      National Institute of Advanced Industrial Science and Technology
  •  データ駆動科学における量子物理・化学的に解釈可能な深層学習手法の開発とその検証Principal Investigator

    • Principal Investigator
      椿 真史
    • Project Period (FY)
      2020 – 2022
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 61030:Intelligent informatics-related
    • Research Institution
      National Institute of Advanced Industrial Science and Technology
  •  Data-Driven Descriptor Generation and its Application to Prediction of Organic Synthetic and Catalytic Reactions

    • Principal Investigator
      矢田 陽
    • Project Period (FY)
      2020 – 2022
    • Research Category
      Grant-in-Aid for Scientific Research (B)
    • Review Section
      Basic Section 33020:Synthetic organic chemistry-related
    • Research Institution
      National Institute of Advanced Industrial Science and Technology
  •  Deep representation learning for drugs and proteins with neural networksPrincipal Investigator

    • Principal Investigator
      Tsubaki Masashi
    • Project Period (FY)
      2017 – 2018
    • Research Category
      Grant-in-Aid for Research Activity Start-up
    • Research Field
      Life / Health / Medical informatics
    • Research Institution
      National Institute of Advanced Industrial Science and Technology

All 2021 2020 2019 2018 2017

All Journal Article Presentation Patent

  • [Journal Article] Quantum deep descriptor: Physically informed transfer learning from small molecules to polymers2021

    • Author(s)
      Masashi Tsubaki and Teruyasu Mizoguchi
    • Journal Title

      Journal of Chemical Theory and Computation

      Volume: 17 Pages: 7814-7821

    • DOI

      10.1021/acs.jctc.1c00568

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-20K19876
  • [Journal Article] On the equivalence of molecular graph convolution and molecular wave function with poor basis set2020

    • Author(s)
      Masashi Tsubaki and Teruyasu Mizoguchi
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 33

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K19876
  • [Journal Article] Quantum Deep Field: Data-Driven Wave Function, Electron Density Generation, and Atomization Energy Prediction and Extrapolation with Machine Learning2020

    • Author(s)
      Masashi Tsubaki and Teruyasu Mizoguchi
    • Journal Title

      Physical Review Letters

      Volume: 125 Pages: 076402-076402

    • DOI

      10.1103/physrevlett.125.206401

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-20K19876, KAKENHI-PLANNED-19H05787, KAKENHI-PROJECT-20H02747
  • [Journal Article] On the equivalence of molecular graph convolution and molecular wave function with poor basis set2020

    • Author(s)
      Masashi Tsubaki、Teruyasu Mizoguchi
    • Journal Title

      Advances in Neural Information Processing Systems 33 (NeurIPS 2020)

      Volume: 33 Pages: 1982-1993

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-20H02747
  • [Journal Article] Learning excited states from ground states by using an artificial neural network2020

    • Author(s)
      Kiyohara Shin、Tsubaki Masashi、Mizoguchi Teruyasu
    • Journal Title

      npj Comp. Mater.

      Volume: 6 Pages: 1-6

    • DOI

      10.1038/s41524-020-0336-3

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PLANNED-19H05787, KAKENHI-PROJECT-20H02747, KAKENHI-PROJECT-20J00773, KAKENHI-PROJECT-19H00818
  • [Journal Article] Quantitative estimation of properties from core-loss spectrum via neural network2019

    • Author(s)
      Shin Kiyohara, Masashi Tsubaki, Kunyen Liao, and Teruyasu Mizoguchi
    • Journal Title

      Journal of Physics: Materials

      Volume: 1 Pages: 1-2

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H07392
  • [Journal Article] Mean-field theory of Graph Neural Networks in Graph Partitioning2018

    • Author(s)
      Tatsuro Kawamoto, Masashi Tsubaki, and Tomoyuki Obuchi
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 1 Pages: 1-2

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H07392
  • [Journal Article] Compound-protein Interaction Prediction with End-to-end Learning of Neural Networks for Graphs and Sequences2018

    • Author(s)
      Masashi Tsubaki, Kentaro Tomii, and Jun Sese
    • Journal Title

      Bioinformatics

      Volume: 35 Pages: 309-318

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H07392
  • [Journal Article] Fast and Accurate Molecular Property Prediction: Learning Atomic Interactions and Potentials with Neural Networks2018

    • Author(s)
      Masashi Tsubaki and Teruyasu Mizoguchi
    • Journal Title

      The Journal of Physical Chemistry Letters

      Volume: 9 Pages: 5733-5741

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H07392
  • [Patent] 物性予測方法及び物性予測装置2020

    • Inventor(s)
      椿真史
    • Industrial Property Rights Holder
      国立研究開発法人産業技術総合研究所
    • Industrial Property Rights Type
      特許
    • Filing Date
      2020
    • Data Source
      KAKENHI-PROJECT-20K19876
  • [Presentation] 創薬と新材料開発のための人工知能2021

    • Author(s)
      椿真史
    • Organizer
      情報処理学会全国大会 2021
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K19876
  • [Presentation] 深層学習に基づく波動関数・電子構造の記述子表現と転移学習への応用依頼講演2021

    • Author(s)
      椿真史
    • Organizer
      日本化学会 第101回春季大会
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K19876
  • [Presentation] 深層学習に基づく波動関数・電子構造の記述子表現と転移学習への応用2021

    • Author(s)
      椿 真史
    • Organizer
      日本化学会 第101春季年会 (2021)
    • Invited
    • Data Source
      KAKENHI-PROJECT-20H02747
  • [Presentation] 深層学習に基づく波動関数・電子構造の記述子表現と転移学習への応用2021

    • Author(s)
      椿真史
    • Organizer
      日本化学会春季年会 2021
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K19876
  • [Presentation] 創薬と新材料開発のための人工知能2021

    • Author(s)
      椿 真史
    • Organizer
      情報処理学会全国大会 2021
    • Invited
    • Data Source
      KAKENHI-PROJECT-20H02747
  • [Presentation] 量子化学計算のための深層学習技術の基礎と応用2021

    • Author(s)
      椿真史
    • Organizer
      顕微鏡計測インフォマティックス研究部会
    • Invited
    • Data Source
      KAKENHI-PROJECT-20K19876
  • [Presentation] 深層学習を用いた化合物とタンパク質の相互作用予測2018

    • Author(s)
      椿真史
    • Organizer
      創薬インフォマティクス研究会
    • Invited
    • Data Source
      KAKENHI-PROJECT-17H07392
  • [Presentation] End-to-end Learning of Graph Neural Networks for Latent Molecular Representations2017

    • Author(s)
      Masashi Tsubaki
    • Organizer
      Advances in Neural Information Processing Systems (NIPS 2017) Workshop, Machine Learning for Molecules and Materials,
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-17H07392
  • 1.  矢田 陽 (70619965)
    # of Collaborated Projects: 2 results
    # of Collaborated Products: 0 results
  • 2.  Asho Hideki
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 3.  Kanemura Atsunori
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 4.  溝口 照康
    # of Collaborated Projects: 0 results
    # of Collaborated Products: 2 results

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