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Sonoda Sho  園田 翔

Researcher Number 00801218
Other IDs
  • ORCIDhttps://orcid.org/0000-0001-7242-4740
Affiliation (Current) 2025: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 上級研究員
Affiliation (based on the past Project Information) *help 2024: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 上級研究員
2021: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 研究員
2018 – 2020: 国立研究開発法人理化学研究所, 革新知能統合研究センター, 特別研究員
Review Section/Research Field
Principal Investigator
Basic Section 61030:Intelligent informatics-related
Except Principal Investigator
Medium-sized Section 60:Information science, computer engineering, and related fields
Keywords
Principal Investigator
機械学習 / 最適輸送理論 / 脳波 / 最適輸送 / 粒子フィルタ / 確率的数値解析 / 大域最適 / 深層ニューラルネット / リッジレット解析 / ベゾフ空間 … More / 量子計算機 / 局所ラデマッハ複雑度 / ODE-Net / 近似下限 / ランダム特徴量 / オーバーパラメトライズ / ラドン変換 / 連続神経場 / 量子機械学習 / 調和解析 / 零空間 / 群畳み込み / 非コンパクト対称空間 / カーネル求積 / Neural ODE / リッジレット変換 / 積分表現理論 / ホワイトボックス化 / ニューラルネット … More
Except Principal Investigator
再生核Hilbert空間 / Besov空間 / Koopman作用素 / 力学系 / 深層学習 Less
  • Research Projects

    (2 results)
  • Research Products

    (75 results)
  • Co-Researchers

    (3 People)
  •  Deepening the analysis of deep learning through functional space theory

    • Principal Investigator
      石川 勲
    • Project Period (FY)
      2024 – 2027
    • Research Category
      Grant-in-Aid for Challenging Research (Pioneering)
    • Review Section
      Medium-sized Section 60:Information science, computer engineering, and related fields
    • Research Institution
      Ehime University
  •  Transportation analysis of deep neural networksPrincipal Investigator

    • Principal Investigator
      Sonoda Sho
    • Project Period (FY)
      2018 – 2021
    • Research Category
      Grant-in-Aid for Early-Career Scientists
    • Review Section
      Basic Section 61030:Intelligent informatics-related
    • Research Institution
      Institute of Physical and Chemical Research

All 2022 2021 2020 2019 2018

All Journal Article Presentation

  • [Journal Article] Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis2022

    • Author(s)
      Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
    • Journal Title

      Proceedings of the 39th International Conference on Machine Learning

      Volume: -

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Journal Article] ニューラルネットの関数解析的方法と無限次元零空間2021

    • Author(s)
      園田翔
    • Journal Title

      日本統計学会誌

      Volume: 50 Pages: 285-316

    • NAID

      130007995101

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Journal Article] Differentiable Multiple Shooting Layers2021

    • Author(s)
      Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 34 Pages: 16532-16544

    • Peer Reviewed / Open Access / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Journal Article] Ridge Regression with Over-Parametrized Two-Layer Networks Converge to Ridgelet Spectrum2021

    • Author(s)
      S. Sonoda, I. Ishikawa, M. Ikeda
    • Journal Title

      Proceedings of The 24th International Conference on Artificial Intelligence and Statistics

      Volume: 130 Pages: 2674-2682

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Journal Article] Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions2020

    • Author(s)
      H. Yamasaki, S. Subramanian, S. Sonoda, M. Koashi
    • Journal Title

      Advances in Neural Information Processing Systems

      Volume: 33 Pages: 13674-13687

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Journal Article] Transport Analysis of Infinitely Deep Neural Network2019

    • Author(s)
      Sho Sonoda, Noboru Murata
    • Journal Title

      Journal of Machine Learning Research

      Volume: 20 Pages: 1-52

    • Peer Reviewed / Open Access
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Journal Article] 生成・消滅過程に基づくEEGデータの電流ダイポール推定2018

    • Author(s)
      中村圭太, 園田翔, 日野英逸, 川崎真弘, 赤穂昭太郎, 村田昇
    • Journal Title

      研究報告数理モデル化と問題解決(MPS)

      Volume: 2018-MPS-118 Pages: 1-8

    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Journal Article] EEG dipole source localization with information criteria for multiple particle filters2018

    • Author(s)
      Sonoda Sho, Nakamura Keita, Kaneda Yuki, Hino Hideitsu, Akaho Shotaro, Murata Noboru, Miyauchi Eri, Kawasaki Masahiro
    • Journal Title

      Neural Networks

      Volume: 108 Pages: 68-82

    • DOI

      10.1016/j.neunet.2018.08.008

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18K18113, KAKENHI-PROJECT-18H03304
  • [Journal Article] Localizing Current Dipoles from EEG Data Using a Birth-Death Process2018

    • Author(s)
      Nakamura Keita, Sonoda Sho, Hino Hideitsu, Kawasaki Masahiro, Akaho Shotaro, Murata Noboru
    • Journal Title

      2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

      Volume: 1 Pages: 2645-2651

    • DOI

      10.1109/bibm.2018.8621504

    • Peer Reviewed
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Fully-Connected Network on Noncompact Symmetric Space and Ridgelet Transform based on Helgason-Fourier Analysis2022

    • Author(s)
      Sho Sonoda, Isao Ishikawa, Masahiro Ikeda
    • Organizer
      The 39th International Conference on Machine Learning (ICML2022)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 積分表現でニューラルネットを理解する2021

    • Author(s)
      園田翔
    • Organizer
      2021年度第5回マス・フォア・イノベーションセミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Ridge Regression with Over-Parametrized Two-Layer Networks Converge to Ridgelet Spectrum2021

    • Author(s)
      S. Sonoda, I. Ishikawa, M. Ikeda
    • Organizer
      The 24th International Conference on Artificial Intelligence and Statistics (AISTATS2021)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] ニューラルネットの零空間の精密構造と統計的役割2021

    • Author(s)
      園田翔, 石川勲, 池田正弘
    • Organizer
      2021年度 統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Regression and Classification with Optimized Random Features: Applications of Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rankness Assumptions2021

    • Author(s)
      H. Yamasaki, S. Subramanian, S. Sonoda and M. Koashi
    • Organizer
      21th Asian Quantum Information Science Conference (AQIS2021)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Differentiable Multiple Shooting Layers2021

    • Author(s)
      Stefano Massaroli, Michael Poli, Sho Sonoda, Taiji Suzuki, Jinkyoo Park, Atsushi Yamashita, Hajime Asama
    • Organizer
      The 35th Neural Information Processing Systems (NeurIPS 2021)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 重み付きSobolev空間におけるニューラルネット積分表現作用素の有界性2021

    • Author(s)
      園田翔, 石川勲, 池田正弘
    • Organizer
      実解析学シンポジウム2021
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Quantum algorithm for sampling optimal random features2021

    • Author(s)
      S.Sonoda, H. Yamasaki, S. Subramanian, and M. Koashi
    • Organizer
      RQC-AIP Joint Seminar
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 積分表現ニューラルネットが定める積分方程式の一般解2021

    • Author(s)
      園田翔, 石川勲, 池田正弘
    • Organizer
      日本応用数理学会2021年度年会
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 群畳み込みニューラルネットのリッジレット変換2021

    • Author(s)
      園田翔, 石川勲, 池田正弘
    • Organizer
      第24回 情報論的学習理論ワークショップ(IBIS2021)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Ridgelet transform on the matrix space2021

    • Author(s)
      S.Sonoda, I.Ishikawa, M.Ikeda
    • Organizer
      13th International ISAAC Congress
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Regression and Classification with Optimized Random Features: Applications of Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rankness Assumptions2021

    • Author(s)
      H. Yamasaki, S. Subramanian, S. Sonoda and M. Koashi
    • Organizer
      Quantum Techniques in Machine Learning (QTML) 2021
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Ghosts in Neural Networks2021

    • Author(s)
      園田翔
    • Organizer
      第1回AI数理セミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 非コンパクト対称空間上の連続ニューラルネットとそのリッジレット変換2021

    • Author(s)
      園田翔, 石川勲, 池田正弘
    • Organizer
      2021年度応用数学合同研究集会
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Harmonic Analysis for Neural Networks and its Applications2020

    • Author(s)
      S. Sonoda
    • Organizer
      Applied and Computational Math Seminar, National University of Singapore (online)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions2020

    • Author(s)
      H. Yamasaki, S. Subramanian, S. Sonoda, M. Koashi
    • Organizer
      20th Asian Quantum Information Science Conference (AQIS 2020)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Learning with Optimized Random Features: Exponential Speedup by Quantum Machine Learning without Sparsity and Low-Rank Assumptions2020

    • Author(s)
      H. Yamasaki, S. Subramanian, S. Sonoda, M. Koashi
    • Organizer
      The 34th Neural Information Processing Systems (NeurIPS 2020)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] ランダムニューラルネットの近似下限評価2020

    • Author(s)
      園田翔, Ming Li
    • Organizer
      2020年度 統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 連続ニューラルネットのリッジレット変換による解析2020

    • Author(s)
      園田翔
    • Organizer
      2020年度第2回明治非線型数理セミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Characterizing Deep Learning Solutions by Using Ridgelet Transform2020

    • Author(s)
      S. Sonoda
    • Organizer
      Differential Equations for Data Science 2021 (DEDS2021)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] オーバーパラメトライズされた有限ニューラルネットの最適解2020

    • Author(s)
      園田翔, 石川勲, 池田正弘
    • Organizer
      第23回 情報論的学習理論ワークショップ(IBIS2020)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 積分幾何学に基づくニューラルネットの新しい再構成公式2020

    • Author(s)
      園田翔, 石川勲, 池田正弘
    • Organizer
      第23回 情報論的学習理論ワークショップ(IBIS2020)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層学習を微分方程式で記述する2020

    • Author(s)
      園田翔
    • Organizer
      第41回IBISML研究会・企画セッション「ダイナミクスと機械学習の接点」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] A New Reconstruction Formula of Neural Networks based on Radon Transform and Its Applications2020

    • Author(s)
      S. Sonoda
    • Organizer
      The 1st Machine Learning Zoom Seminar
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Functional Analysis Methods for Neural Network Theory2020

    • Author(s)
      S. Sonoda
    • Organizer
      The 20th AIP Open Seminar
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 積分幾何学に基づくニューラルネットのパラメータ分布再考2020

    • Author(s)
      園田翔
    • Organizer
      第23回 情報論的学習理論ワークショップ(IBIS2020)・企画セッション「学習理論」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Continuous Model of Deep Neural Networks2019

    • Author(s)
      Sho Sonoda
    • Organizer
      Theory towards Brains, Machines and Minds, RIKEN CBS
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] ニューラルネットの連続モデル2019

    • Author(s)
      園田翔
    • Organizer
      福岡大学
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Continuous Model of Deep Neural Networks2019

    • Author(s)
      Sho Sonoda
    • Organizer
      South China Normal University
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 最適制御にもとづく機械学習の試み2019

    • Author(s)
      園田翔
    • Organizer
      Workshop on Transport at Metropolitan
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 連続ニューラルネットの諸相2019

    • Author(s)
      園田翔
    • Organizer
      情報系 WINTER FESTA Episode 5
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 連続モデルによるニューラルネットの解析2019

    • Author(s)
      園田翔
    • Organizer
      金沢大学 第2回微分方程式とデータサイエンス研究会
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層ニューラルネットについて2019

    • Author(s)
      園田翔
    • Organizer
      第6回日本橋確率論セミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Barron評価を達成するニューラルネットの構成法2019

    • Author(s)
      園田翔
    • Organizer
      日本応用数理学会2019年度年会
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層学習入門2019

    • Author(s)
      園田翔
    • Organizer
      理研AIP数学系合同セミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] ニューラルネットの連続モデル2019

    • Author(s)
      園田翔
    • Organizer
      大阪大学 数理・データ科学セミナー 数理モデルセミナーシリーズ 第24回
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Generalized kernel quadrature for synthesizing neural networks2019

    • Author(s)
      Sho Sonoda
    • Organizer
      Generalized kernel quadrature for synthesizing neural networks Data Science, Statistics & Visualization (DSSV2019), a satellite conference of the 62nd World Statistics Congress, promoted by IASC
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] ReLU深層ニューラルネットワークの一般化されたBesov空間での関数近似能力について2019

    • Author(s)
      谷口晃一, 池田正弘, 園田翔, 大野健太, 鈴木大慈
    • Organizer
      第22回 情報論的学習理論ワークショップ(IBIS2019)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層学習の汎化誤差評価2019

    • Author(s)
      園田翔
    • Organizer
      理研AIP数学系合同セミナー
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Continuous Model of Deep Neural Networks2019

    • Author(s)
      Sho Sonoda
    • Organizer
      Peking University
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] ランダム神経場の学習 -NTKによる定式化と実験的検証-2019

    • Author(s)
      渡部海斗, 坂本航太郎, 園田翔, 唐木田亮, 甘利俊一
    • Organizer
      第22回 情報論的学習理論ワークショップ(IBIS2019)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Random neural field learning: Formalization and numerical experiments via NTK2019

    • Author(s)
      Kaito Watanabe, Kota Sakamoto, Ryo Karakida, Sho Sonoda, Shunichi Amari
    • Organizer
      ACML 2019 Workshop on Statistics & Machine Learning Researchers in Japan
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Numerical Integration Method for Training Neural Networks2019

    • Author(s)
      Sho Sonoda
    • Organizer
      The 12th International Conference on Monte Carlo Methods and Applications (MCM2019)
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] カーネル求積による浅いモデルの学習法2019

    • Author(s)
      園田翔
    • Organizer
      2019年度 統計関連学会連合大会
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Fast quantum algorithm for data approximation by optimized random features2019

    • Author(s)
      Hayata Yamasaki, Sathyawageeswar Subramanian, Sho Sonoda, Masato Koashi
    • Organizer
      量子情報技術研究会(QIT)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Stein's method for computing inverse operators2019

    • Author(s)
      Sho Sonoda
    • Organizer
      ICML 2019 Workshop on Stein's Method in Machine Learning and Statistics
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 量子コンピュータによる高速ランダム特徴量サンプリング2019

    • Author(s)
      山崎隼汰, Sathyawageeswar Subramanian, 園田翔
    • Organizer
      第22回 情報論的学習理論ワークショップ(IBIS2019)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Continuous Model of Deep Neural Networks2019

    • Author(s)
      Sho Sonoda
    • Organizer
      IIT-RIKEN Workshop
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Coordinate-free approaches to neural networks2019

    • Author(s)
      Sho Sonoda
    • Organizer
      PAIR-AIP Joint Research Workshop
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層ニューラルネットの数理2018

    • Author(s)
      園田翔
    • Organizer
      津山高専人工知能研究講演会
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Inverse problem in denoising autoencoder2018

    • Author(s)
      園田翔
    • Organizer
      2019 RIMS 共同研究 「偏微分方程式に対する逆問題の数学解析とその周辺」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Integral representation of shallow neural network that attains the global minimum2018

    • Author(s)
      Sho Sonoda, Isai Ishikawa, Masahiro Ikeda, Kei Hagihara, Yoshihiro Sawano, Takuo Matsubara, Noboru Murata
    • Organizer
      The First Japan-Israel Machine Learning Workshop (JIML)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層ニューラルネットの数理2018

    • Author(s)
      園田翔
    • Organizer
      山形大学DS推進室キックオフミーティング
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] カーネル求積による積分変換の計算2018

    • Author(s)
      園田翔
    • Organizer
      第21回 情報論的学習理論ワークショップ(IBIS2018)
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層学習入門2018

    • Author(s)
      園田翔
    • Organizer
      第21回 情報論的学習理論ワークショップ(IBIS2018) チュートリアル
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Mathematical Models of Neural Networks2018

    • Author(s)
      Sho Sonoda
    • Organizer
      Brawijaya University Seminar on Mathematical Analysis and Its Application
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 機械学習と解析学2018

    • Author(s)
      園田翔
    • Organizer
      第3回東京実解析セミナー
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層学習の基礎理論と発展2018

    • Author(s)
      園田翔
    • Organizer
      第37回日本医用画像工学会大会 (JAMIT2018) シンポジウム2「深層学習の基礎理論と発展」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Continuous Model of Deep Neural Networks2018

    • Author(s)
      Sho Sonoda
    • Organizer
      Invited Lecture at Max Planck Institute for Intelligent Systems
    • Invited / Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 数値積分によるニューラルネットの学習2018

    • Author(s)
      園田翔
    • Organizer
      2018 RIMS 共同研究 「次世代の科学技術を支える数値解析学の基盤整備と応用展開」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 大域最適解を与えるニューラルネットの積分表現2018

    • Author(s)
      園田翔
    • Organizer
      第3回統計・機械学習若手シンポジウム「統計・機械学習の交わりと広がり」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] An explicit expression for the global minimizer network2018

    • Author(s)
      Sho Sonoda, Isai Ishikawa, Masahiro Ikeda, Kei Hagihara, Yoshihiro Sawano, Takuo Matsubara, Noboru Murata
    • Organizer
      ICML 2018 Workshop on Theory of Deep Learning (TDL)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 生成・消滅過程に基づくEEGデータの電流ダイポール推定2018

    • Author(s)
      中村圭太, 園田翔, 日野英逸, 川崎真弘, 赤穂昭太郎, 村田昇
    • Organizer
      第33回 IBISML研究会
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層ニューラルネットの数理モデル2018

    • Author(s)
      園田翔
    • Organizer
      名古屋工業大学講演会「最適輸送と機械学習理論の周辺」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] 深層ニューラルネット理論の近況2018

    • Author(s)
      園田翔
    • Organizer
      日本数学会2018年度秋季総合分科会 応用数学特別セッション「機械学習の数学的課題: 深層学習の理論を中心に」
    • Invited
    • Data Source
      KAKENHI-PROJECT-18K18113
  • [Presentation] Localizing Current Dipoles from EEG Data Using a Birth Death Process2018

    • Author(s)
      Nakamura Keita, Sonoda Sho, Hino Hideitsu, Kawasaki Masahiro, Akaho Shotaro, Murata Noboru
    • Organizer
      IEEE BIBM 2018 workshop on Machine Learning for EEG Signal Processing (MLESP 2018)
    • Int'l Joint Research
    • Data Source
      KAKENHI-PROJECT-18K18113
  • 1.  石川 勲 (80804236)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 2.  池田 正弘 (00749690)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results
  • 3.  谷口 晃一 (60856235)
    # of Collaborated Projects: 1 results
    # of Collaborated Products: 0 results

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