Graduate School of Social Data Science
MOTOTAKE Yoh-ichi

Papers

1. Autoregressive with Slack Time Series Model for Forecasting a Partially-Observed Dynamical Time Series (Peer-reviewed)
A. Okuno, Y. Morishita, Y. Mototake
IEEE Access 2024.2
doi
2. Search for high-creep-strength welding conditions considering HAZ shape factors for 2 1/4Cr-1Mo steel (Peer-reviewed)
Hitoshi IZUNO, Masahiko Demura, Masayoshi Yamazaki, Satoshi Minamoto, Junya Sakurai, Kenji Nagata, Yoh-ichi Mototake, Daisuke Abe, Keisuke Torigata
Welding in the World 2024.2
3. Revealing the Mechanism of Large-scale Gradient Systems Using a Neural Reduced Potential (Peer-reviewed)
Shunya Tsuji, Ryo Murakami, Hayaru Shouno, Yoh-ichi Mototake
NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences 2023.12
4. Quantification of Galaxy Distribution with Topological Data Analysis and Detection of the Baryon Acoustic Oscillation (Peer-reviewed)
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 Vol.71,No.2,pp.159-187 2023.12
5. Extracting Nonlinear Symmetries From Trained Neural Networks on Dynamics Data (Peer-reviewed)
Yoh-ichi Mototake
NeurIPS 2023 Workshop: AI for Science from Theory to Practice 2023.12
6. Quantifying physical insights cooperatively with exhaustive search for Bayesian spectroscopy of X-ray photoelectron spectra (Peer-reviewed)
Hiroyuki Kumazoe, Kazunori Iwamitsu, Masaki Imamura, Kazutoshi Takahashi, Yoh-ichi Mototake, Masato Okada, Ichiro Akai
Scientific Reports Vol.13,No.1 2023.8
doi Link Link
7. Quantitative prediction of fracture toughness (<i>K</i><sub>I<i>c</i></sub>) of polymer by fractography using deep neural networks (Peer-reviewed)
Y. Mototake, K. Ito, M. Demura
Science and Technology of Advanced Materials: Methods Vol.2,No.1,pp.310-321 2022.9
doi Link
8. Interpretable conservation law estimation by deriving the symmetries of dynamics from trained deep neural networks (Peer-reviewed)
Yoh-ichi Mototake
Physical Review E Vol.103,pp.033303- 2021.3
9. Comparison of neuronal responses in primate inferior-temporal cortex and feed-forward deep neural network model with regard to information processing of faces (Peer-reviewed)
Narihisa Matsumoto, Yoh-ichi Mototake, Kenji Kawano, Masato Okada, Yasuko Sugase-Miyamoto
Journal of Computational Neuroscience 2021.2
doi
10. Topological Data Analysis of Domain Pattern Formation in Materials (Peer-reviewed)
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 Vol.10,No.3,pp.108-119 2021
Link
11. Free Energy Estimation of Metastable Structures of Block Copolymers using Topological Data Analysis (Peer-reviewed)
Yoh-ichi Mototake, Sadato Yamanaka, Takeshi Aoyagi, Takaaki Ohnishi, Kenji Fukumizu
Journal of Computer Chemistry Japan Vol.19,No.4,pp.169-171 2021
12. A universal Bayesian inference framework for complicated creep constitutive equations (Peer-reviewed)
Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada
Scientific Reports 2020.6
13. Development of spectral decomposition based on Bayesian information criterion with estimation of confidence interval (Peer-reviewed)
Hiroshi Shinotsuka, Hideki Yoshikawa, Yoh-ichi Mototake, Hayaru Shouno, Masato Okada, Kenji Nagata
Science and Technology of Advanced Materials 2020.6
14. Data-based selection of creep constitutive models for high-Cr heat-resistant steel (Peer-reviewed)
IZUNO, Hitoshi, Demura, Masahiko, TABUCHI, Masaaki, Mototake, Yoh-ichi, Okada, Masato
Science and Technology of Advanced Materials Vol.21,No.1,pp.219-228 2020
15. Topological Data Analysis for microdomain patternsof Block Copolymer (Peer-reviewed)
Yoh-ichi Mototake, Sadato Yamanaka, Takeshi Aoyagi, Takaaki Ohnishi, Kenji Fukumizu
Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications 2020
16. Revealing the existence of the ontological commitment in fish schools (Peer-reviewed)
Takayuki Niizato, Kotaro Sakamoto, Yoh-ichi Mototake, Hisashi Murakami, Takenori Tomaru, Tomotaro Hoshika, Toshiki Fukushima
Artif Life Robotics Vol.25,pp.633-633–642 2020
doi
17. Towards a Geometrical Understanding of Physical Phenomena via Extraction of Data Manifolds using Generative Models (Peer-reviewed)
Kotaro Sakamoto, Yuichiro Mori, Yoh-ichi Mototake
Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications 2020
18. Finding continuity and discontinuity in fish schools via integrated information theory. (Peer-reviewed)
Takayuki Niizato, Kotaro Sakamoto, Yoh-Ichi Mototake, Hisashi Murakami, Takenori Tomaru, Tomotaro Hoshika, Toshiki Fukushima
PloS one Vol.15,No.2,pp.e0229573- 2020
doi
19. Four-types of IIT-induced group integrity of Plecoglossus altivelis (Peer-reviewed)
Takayuki Niizato, Kotaro Sakamoto, Yoh-ichi Mototake, Hisashi Murakami, Yuta Nishiyama, Toshiki Fukushima
Entropy Vol.22,No.7,pp.726 2020
doi Link Link
20. Universal Framework of Bayesian Creep Model Selection for Steel, (Peer-reviewed)
Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada
Materials Research Meeting 2019 2019.12
21. Universal Framework of Bayesian Creep Model Selection for Steel, (Peer-reviewed)
Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada
International Conference on Computational & Experimental Engineering and Sciences 2019.3
22. Descriptor Extraction on Inherent Creep Strength of Carbon Steels by Exhaustive Search (Peer-reviewed)
Junya Sakurai, Junya Inoue, Masahiko Demura, Yoichi Mototake, Masato Okada, Masayoshi Yamazaki
International Conference on Computational & Experimental Engineering and Sciences 2019
23. Conservation Law Estimation by Extracting the Symmetry of a Dynamical System Using a DNN (Peer-reviewed)
Yoh-ichi Mototake
NeurIPS2019 Workshop on Machine Learning and the Physical Sciences(ML4PS) 2019
24. Semi-flat minima and saddle points by embedding neural networks to overparameterization (Peer-reviewed)
Kenji Fukumizu, Shoichiro Yamaguch, Yoh-ichi Mototake, Mirai Tanaka
Advances in Neural Information Processing Systems (NeurIPS) 2019
25. Bayesian Hamiltonian Selection in X-ray Photoelectron Spectroscopy (Peer-reviewed)
Yoh-ichi Mototake, Masaichiro Mizumaki, Ichiro Akai, Masato Okada
Journal of the Physical Society of Japan Vol.88,No.3 2019
doi
26. Bayesian Spectral Deconvolution Based on Poisson Distribution: Bayesian Measurement and Virtual Measurement Analytics (VMA) (Peer-reviewed)
Kenji Nagata, Yoh-ichi Mototake, Rei Muraoka, Takehiko Sasaki, Masato Okada
Journal of the Physical Society of Japan Vol.88,No.4,pp.044003 2019
doi Link
27. Creep Model Selection for Grade 91 Steel Using Data Scientific Method (Peer-reviewed)
Hitoshi Izuno, Masahiko Demura, Masaaki Tabuchi, Yohichi Mototake, Masato Okada
International Conference on Computational & Experimental Engineering and Sciences 2019
28. レプリカ交換モンテカルロ法を用いたMixture of Experts モデルにおけるベイズ推論 (Peer-reviewed)
松平京介, 永田賢二, 本武陽一, 岡田真人
情報処理学会論文誌数理モデル化と応用 (TOM) 2019
29. Heap Paradox in Fish Schools (Peer-reviewed)
Takayuki Niizato, Kotaro Sakamoto, Yoh-Ichi Mototake, Hisashi Murakami, Yuta Nishiyama, Toshiki Fukushima
SWARM2019 2019
30. Spectral deconvolution through bayesian LARS-OLS (Peer-reviewed)
Yoh-ichi Mototake, Yasuhiko Igarashi, Hikaru Takenaka, Kenji Nagata, Masato Okada
Journal of the Physical Society of Japan Vol.87,No.11 2018
31. Life as an emergent phenomenon: studies from a large-scale boid simulation and web data (Peer-reviewed)
Takashi Ikegami, Yoh-ichi Mototake, Shintaro Kobori, Mizuki Oka, Yasuhiro Hashimoto
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES Vol.375,No.2109 2017.12
doi
32. Revisiting Classification of Large Scale Flocking (Peer-reviewed)
Norihiro Maruyama, Yasuhiro Hashimoto, Yhoichi Mototake, Daichi Saito, Takashi Ikegami
The 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics 2017
33. Creating an in-group relation between humans and agents (Peer-reviewed)
Yoh Ichi Mototake, Haruaki Fukuda, Kazuhiro Ueda
Transactions of the Japanese Society for Artificial Intelligence Vol.31,No.6,pp.AI30-J_1-10- 2016
doi
34. The dynamics of deep neural networks (Peer-reviewed)
Yhoichi Mototake, Takashi Ikegami
the Twentieth International Symposium on Artificial Life and Robotics 2015
35. A Simulation Study of Large Scale Swarms (Peer-reviewed)
Yhoichi Mototake, Takashi Ikegami
The 1st International Symposium on Swarm Behavior and Bio-Inspired Robotics 2015 2015

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Misc.

1. 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) Vol.34th 2021
2. 位相的データ分析法による材料構造形成過程の分析 (Peer-reviewed)
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 Vol.10,No.3 2021
3. 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) Vol.74,No.1 2019
4. Detecting Large Scale Flocking and Development of Spatio-Temporal Patterns
丸山 典宏, 橋本 康弘, 本武 陽一, 斉藤 大地, 池上 高志
システム制御情報学会研究発表講演会講演論文集 Vol.62,pp.3p- 2018.5
Link
5. 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 Vol.59,No.1,pp.42-47 2017
6. Analysis of Multimodal Deep Neural Networks : Towards the Elucidation of The Modality Integration Mechanism
本武 陽一, 池上 高志
電子情報通信学会技術研究報告 = IEICE technical report : 信学技報 Vol.116,No.300,pp.369-373 2016.11
Link

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Presentations

No. Name of subject/Conference Name Year Site
1. 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(ディープラーニングと物理学2020 オンライン)
Holding date :
Presentation date : 2020.7.30
2. 第2回日米独先端科学(JAGFoS)シンポジウム(第2回日米独先端科学(JAGFoS)シンポジウム)
Holding date :
Presentation date : 2019.10
3. The 4th Workshop on Self-Organization and Robustness of Evolving Many-Body Systems(The 4th Workshop on Self-Organization and Robustness of Evolving Many-Body Systems)
Holding date :
Presentation date : 2019.3
4. 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(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)
Holding date :
Presentation date : 2018
5. 神経回路学会時限研究会「ニューラルネットの温故知新」(神経回路学会時限研究会「ニューラルネットの温故知新」)
Holding date :
Presentation date : 2016
6. 第11回全脳アーキテクチャ勉強会(第11回全脳アーキテクチャ勉強会)
Holding date :
Presentation date : 2015

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Awards

No. Award name Year
1. The 3rd International Symposium on Swarm Behavior and Bio-Inspired Robotics, Best Paper Award Finalists 2019
2. 脳学際研究部門第1回公開シンポジウム 最優秀発表賞 2017
3. 2016 Annual Conference Award 2016
4. The First International Symposium on Swarm Behavior and Bio-Inspired Robotics, Best Student Paper Award Finalists 2015

Research Projects

No. Research subject Research item(Awarding organization, System name) Year
1. 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

( Awarding organization: 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) System name: 未踏チャレンジ2050 )
2022.8 - 2025.7
2. Development of machine learning methods for discovering symmetries in pattern dynamics
Grant-in-Aid for Early-Career Scientists
( Awarding organization: Japan Society for the Promotion of Science System name: Grants-in-Aid for Scientific Research Grant-in-Aid for Early-Career Scientists )
2022.4 - 2027.3
3. 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
さきがけ
( Awarding organization: 国立研究開発法人科学技術振興機構 System name: 戦略的創造研究推進事業(さきがけ) )
2021.10 - 2025.3
4. Constructing a reduced model of a pattern formation process on the basis of topological data analysis
Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area)
( Awarding organization: Japan Society for the Promotion of Science System name: Grants-in-Aid for Scientific Research Grant-in-Aid for Scientific Research on Innovative Areas (Research in a proposed research area) )
2020.4 - 2022.3
5. 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
一般研究2
( Awarding organization: 統計数理研究所 System name: 統計数理研究所共同利用 )
2020.4 - 2021.3
6. TDAによる強磁性体磁区パターン形成過程の分析
一般研究2
( Awarding organization: 統計数理研究所 System name: 統計数理研究所共同利用 )
2020.4 - 2021.3

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