Yoh-ichi Mototake

Profile Information

Affiliation: Associate Professor, Hitotsubashi University

Degree: Ph.D(Mar, 2016, The University of Tokyo)

J-GLOBAL ID: 201901012105162948
researchmap Member ID: B000375875

Research Interests

Research Areas

Research History

Jan, 2023 - Present

Associate professor, Graduate School of Social Data Science, Hitotsubashi University
Apr, 2019 - Dec, 2022

The Institute of Statistical Mathematics
Apr, 2016 - Mar, 2019

The University of Tokyo

Education

Apr, 2013 - Mar, 2016

Master Course of Department of General Systems Studies, Graduate School of Arts and Sciences, The University of Tokyo
Apr, 2010 - Mar, 2013

Master Course of Department of General Systems Studies, College of Arts and Sciences, The University of Tokyo
Apr, 2008 - Mar, 2010

Master Course of Department of Physics, Faculty of Science, Hokkaido University
Apr, 2004 - Mar, 2008

Department of physics, Faculty of Science, Tohoku University

Awards

2019

The 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics, Best Paper Award Finalists, SWARM2019

Takayuki Niizato, Kotaro Sakamoto, Yoh-Ichi Mototake, Hisashi Murakami, Yuta Nishiyama, Toshiki Fukushima
2017

脳学際研究部門第1回公開シンポジウム最優秀発表賞, 東京理科大学

Yohichi Mototake
2016

2016 Annual Conference Award, 日本人工知能学会

本武陽一
2015

The First International Symposium on Swarm Behavior and Bio-Inspired Robotics, Best Student Paper Award Finalists, SWARM 2015

本武陽一, 池上高志

Papers

Search for high-creep-strength welding conditions considering HAZ shape factors for 2 1/4Cr-1Mo steel

Hitoshi IZUNO, Masahiko Demura, Masayoshi Yamazaki, Satoshi Minamoto, Junya Sakurai, Kenji Nagata, Yoh-ichi Mototake, Daisuke Abe, Keisuke Torigata

Welding in the World, Feb, 2024 Peer-reviewed
Autoregressive with Slack Time Series Model for Forecasting a Partially-Observed Dynamical Time Series

A. Okuno, Y. Morishita, Y. Mototake

IEEE Access, Feb, 2024 Peer-reviewed
Quantification of Galaxy Distribution with Topological Data Analysis and Detection of the Baryon Acoustic Oscillation

Tsutomu T. Takeuchi, Kai T. Kono, Suchetha Cooray, Atsushi J. Nishizawa, Koya Murakami, Hai-Xia Ma, Yoh-Ichi Mototake

Proceedings of the Institute of Statistical Mathematics, 71(2) 159-187, Dec, 2023 Peer-reviewed
Extracting Nonlinear Symmetries From Trained Neural Networks on Dynamics Data

Yoh-ichi Mototake

NeurIPS 2023 Workshop: AI for Science from Theory to Practice, Dec, 2023 Peer-reviewed
Revealing the Mechanism of Large-scale Gradient Systems Using a Neural Reduced Potential

Shunya Tsuji, Ryo Murakami, Hayaru Shouno, Yoh-ichi Mototake

NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences, Dec, 2023 Peer-reviewed
Quantifying physical insights cooperatively with exhaustive search for Bayesian spectroscopy of X-ray photoelectron spectra

Hiroyuki Kumazoe, Kazunori Iwamitsu, Masaki Imamura, Kazutoshi Takahashi, Yoh-ichi Mototake, Masato Okada, Ichiro Akai

Scientific Reports, 13(1), Aug 14, 2023 Peer-reviewed
Quantitative prediction of fracture toughness (K_Ic) of polymer by fractography using deep neural networks

Y. Mototake, K. Ito, M. Demura

Science and Technology of Advanced Materials: Methods, 2(1) 310-321, Sep 5, 2022 Peer-reviewed
Interpretable conservation law estimation by deriving the symmetries of dynamics from trained deep neural networks

Yoh-ichi Mototake

Physical Review E, 103 033303, Mar, 2021 Peer-reviewed
Comparison of neuronal responses in primate inferior-temporal cortex and feed-forward deep neural network model with regard to information processing of faces

Narihisa Matsumoto, Yoh-ichi Mototake, Kenji Kawano, Masato Okada, Yasuko Sugase-Miyamoto

Journal of Computational Neuroscience, Feb, 2021 Peer-reviewed
Topological Data Analysis of Domain Pattern Formation in Materials

10(3) 108-119, 2021 Peer-reviewedInvited
Free Energy Estimation of Metastable Structures of Block Copolymers using Topological Data Analysis

Yoh-ichi Mototake, Sadato Yamanaka, Takeshi Aoyagi, Takaaki Ohnishi, Kenji Fukumizu

Journal of Computer Chemistry Japan, 19(4) 169-171, 2021 Peer-reviewed
A universal Bayesian inference framework for complicated creep constitutive equations

Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada

Scientific Reports, Jun, 2020 Peer-reviewed
Development of spectral decomposition based on Bayesian information criterion with estimation of confidence interval

Hiroshi Shinotsuka, Hideki Yoshikawa, Yoh-ichi Mototake, Hayaru Shouno, Masato Okada, Kenji Nagata

Science and Technology of Advanced Materials, Jun, 2020 Peer-reviewed
Topological Data Analysis for microdomain patternsof Block Copolymer

Yoh-ichi Mototake, Sadato Yamanaka, Takeshi Aoyagi, Takaaki Ohnishi, Kenji Fukumizu

Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications, 2020 Peer-reviewed
Towards a Geometrical Understanding of Physical Phenomena via Extraction of Data Manifolds using Generative Models

Kotaro Sakamoto, Yuichiro Mori, Yoh-ichi Mototake

Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications, 2020 Peer-reviewed
Revealing the existence of the ontological commitment in fish schools

Takayuki Niizato, Kotaro Sakamoto, Yoh-ichi Mototake, Hisashi Murakami, Takenori Tomaru, Tomotaro Hoshika, Toshiki Fukushima

Artif Life Robotics, 25 633-633–642, 2020 Peer-reviewed
Four-types of IIT-induced group integrity of Plecoglossus altivelis

Takayuki Niizato, Kotaro Sakamoto, Yoh-ichi Mototake, Hisashi Murakami, Yuta Nishiyama, Toshiki Fukushima

Entropy, 22(7) 726-726, 2020 Peer-reviewed
Finding continuity and discontinuity in fish schools via integrated information theory.

Takayuki Niizato, Kotaro Sakamoto, Yoh-Ichi Mototake, Hisashi Murakami, Takenori Tomaru, Tomotaro Hoshika, Toshiki Fukushima

PloS one, 15(2) e0229573, 2020 Peer-reviewed
Data-based selection of creep constitutive models for high-Cr heat-resistant steel

IZUNO, Hitoshi, Demura, Masahiko, TABUCHI, Masaaki, Mototake, Yoh-ichi, Okada, Masato

Science and Technology of Advanced Materials, 21(1) 219-228, 2020 Peer-reviewed
Universal Framework of Bayesian Creep Model Selection for Steel,

Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada

Materials Research Meeting 2019, Dec, 2019 Peer-reviewed

Misc.

位相的データ分析による強磁性体磁区パターン形成過程の分析

本武陽一, 水牧仁一朗, 工藤和恵, 福水健次

日本放射光学会年会・放射光科学合同シンポジウム(Web), 34th, 2021
位相的データ分析法による材料構造形成過程の分析

本武陽一, 水牧仁一朗, 工藤和恵, 福水健次

スマートプロセス学会誌, 10(3), 2021 Peer-reviewedInvited
X線光電子分光におけるベイズ推論によるハミルトニアン選択

本武陽一, 水牧仁一朗, 赤井一郎, 岡田真人

日本物理学会講演概要集(CD-ROM), 74(1), 2019
Detecting Large Scale Flocking and Development of Spatio-Temporal Patterns

62 3p, May 16, 2018
脳情報科学が拓くAIとICT：2．脳情報科学と人工知能 -ネオコグニトロンからDeep Learningへ-

本武陽一, 庄野逸, 田村弘, 岡田真人

情報処理, 59(1) 42-47, 2017
Analysis of Multimodal Deep Neural Networks : Towards the Elucidation of The Modality Integration Mechanism

116(300) 369-373, Nov 16, 2016

Presentations

物理学者と学習機械の効果的な協業に向けて：学習済み深層ニューラルネットワークからの解釈可能な物理法則抽出

本武陽一

ディープラーニングと物理学2020 オンライン, Jul 30, 2020 Invited
第2回日米独先端科学(JAGFoS)シンポジウム

本武陽一

第2回日米独先端科学(JAGFoS)シンポジウム, Oct, 2019 Invited
The 4th Workshop on Self-Organization and Robustness of Evolving Many-Body Systems

本武陽一

The 4th Workshop on Self-Organization and Robustness of Evolving Many-Body Systems, Mar, 2019 Invited
第2回教育・コミュニケーションロボット研究開発シンポジウム

本武陽一

第2回教育・コミュニケーションロボット研究開発シンポジウム, 2018 Invited
神経回路学会時限研究会「ニューラルネットの温故知新」

本武陽一

神経回路学会時限研究会「ニューラルネットの温故知新」, 2016 Invited
第11回全脳アーキテクチャ勉強会

本武陽一

第11回全脳アーキテクチャ勉強会, 2015 Invited

Teaching Experience

Aug, 2024 - Aug, 2024

物理学特別講義 (中央大学大学院理工学研究科物理学専攻)
Aug, 2023 - Aug, 2023

物理情報計測特別講義 (福岡大学理学部物理科学科)
Apr, 2021 - Mar, 2023

データサイエンス実習 (立教大学)
Oct, 2019 - Mar, 2023

データサイエンス・アドバンスド・プログラム (成城大学)
Oct, 2019 - Mar, 2023

データサイエンス応用 (成城大学)
Sep, 2021 - Mar, 2022

Introduction to AI (Hitotsubashi University)
Apr, 2020 - Jul, 2020

数理科学１ (University of Tsukuba)

Professional Memberships

Research Projects

Development of machine learning methods for discovering symmetries in pattern dynamics

Grants-in-Aid for Scientific Research Grant-in-Aid for Early-Career Scientists, Grant-in-Aid for Early-Career Scientists, Japan Society for the Promotion of Science, Apr, 2022 - Mar, 2027
革新的セラミック材料設計のための材料パターン情報学の創成

未踏チャレンジ２０５０, 国立研究開発法人新エネルギー・産業技術総合開発機構（NEDO）, Aug, 2022 - Jul, 2025

本武陽一
解釈可能AIによるパターンダイナミクスの数理構造抽出と材料情報学への応用

戦略的創造研究推進事業（さきがけ）, さきがけ, 国立研究開発法人科学技術振興機構, Oct, 2021 - Mar, 2025

本武陽一
Constructing a reduced model of a pattern formation process on the basis of topological data analysis

Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area), Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area), Japan Society for the Promotion of Science, Apr, 2020 - Mar, 2022
代数幾何的学習理論の物理データ分析への応用手法の検討

統計数理研究所共同利用, 一般研究２, 統計数理研究所, Apr, 2020 - Mar, 2021
TDAによる強磁性体磁区パターン形成過程の分析

統計数理研究所共同利用, 一般研究２, 統計数理研究所, Apr, 2020 - Mar, 2021

Academic Activities

Journal of the Physical Society of Japan

Peer review

Physical Society of Japan, Apr, 2021 - Present
The 24th International Conference on Artificial Intelligence and Statistics (AISTATS2021)

Planning, management, etc.

Apr 13, 2021
International Joint Conferences on Artificial Intelligence (IJCAI 2020)

Peer review

2020
Neural Information Processing Systems (NeurIPS 2020)

Peer review

2020
Neural Information Processing Systems (NeurIPS 2019)

Peer review

2019
電子情報通信学会和文論文誌D

Peer review
Neural Networks

Peer review

Profile Information

Research Interests

Research Areas

Research History

Education

Awards

Papers

Misc.

Presentations

Teaching Experience

Professional Memberships

Research Projects

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