1. |
Autoregressive with Slack Time Series Model for Forecasting a Partially-Observed Dynamical Time Series
(査読有り)
A. Okuno, Y. Morishita, Y. Mototake
IEEE Access 2024年2月
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2. |
Search for high-creep-strength welding conditions considering HAZ shape factors for 2 1/4Cr-1Mo steel
(査読有り)
Hitoshi IZUNO, Masahiko Demura, Masayoshi Yamazaki, Satoshi Minamoto, Junya Sakurai, Kenji Nagata, Yoh-ichi Mototake, Daisuke Abe, Keisuke Torigata
Welding in the World 2024年2月 |
3. |
Revealing the Mechanism of Large-scale Gradient Systems Using a Neural Reduced Potential
(査読有り)
Shunya Tsuji, Ryo Murakami, Hayaru Shouno, Yoh-ichi Mototake
NeurIPS 2023 Workshop: Machine Learning and the Physical Sciences 2023年12月 |
4. |
Extracting Nonlinear Symmetries From Trained Neural Networks on Dynamics Data
(査読有り)
Yoh-ichi Mototake
NeurIPS 2023 Workshop: AI for Science from Theory to Practice 2023年12月 |
5. |
Quantification of Galaxy Distribution with Topological Data Analysis and Detection of the Baryon Acoustic Oscillation
(査読有り)
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巻2号159-187頁 2023年12月 |
6. |
Quantifying physical insights cooperatively with exhaustive search for Bayesian spectroscopy of X-ray photoelectron spectra
(査読有り)
Hiroyuki Kumazoe, Kazunori Iwamitsu, Masaki Imamura, Kazutoshi Takahashi, Yoh-ichi Mototake, Masato Okada, Ichiro Akai
Scientific Reports 13巻1号 2023年8月
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7. |
Quantitative prediction of fracture toughness (<i>K</i><sub>I<i>c</i></sub>) of polymer by fractography using deep neural networks
(査読有り)
Y. Mototake, K. Ito, M. Demura
Science and Technology of Advanced Materials: Methods 2巻1号310-321頁 2022年9月
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8. |
Interpretable conservation law estimation by deriving the symmetries of dynamics from trained deep neural networks
(査読有り)
Yoh-ichi Mototake
Physical Review E 103巻033303-頁 2021年3月 |
9. |
Comparison of neuronal responses in primate inferior-temporal cortex and feed-forward deep neural network model with regard to information processing of faces
(査読有り)
Narihisa Matsumoto, Yoh-ichi Mototake, Kenji Kawano, Masato Okada, Yasuko Sugase-Miyamoto
Journal of Computational Neuroscience 2021年2月
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10. |
Free Energy Estimation of Metastable Structures of Block Copolymers using Topological Data Analysis
(査読有り)
Yoh-ichi Mototake, Sadato Yamanaka, Takeshi Aoyagi, Takaaki Ohnishi, Kenji Fukumizu
Journal of Computer Chemistry Japan 19巻4号169-171頁 2021年 |
11. |
位相的データ分析法による材料構造形成過程の分析
(査読有り)
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巻3号108-119頁 2021年
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12. |
A universal Bayesian inference framework for complicated creep constitutive equations
(査読有り)
Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada
Scientific Reports 2020年6月 |
13. |
Development of spectral decomposition based on Bayesian information criterion with estimation of confidence interval
(査読有り)
Hiroshi Shinotsuka, Hideki Yoshikawa, Yoh-ichi Mototake, Hayaru Shouno, Masato Okada, Kenji Nagata
Science and Technology of Advanced Materials 2020年6月 |
14. |
Finding continuity and discontinuity in fish schools via integrated information theory.
(査読有り)
Takayuki Niizato, Kotaro Sakamoto, Yoh-Ichi Mototake, Hisashi Murakami, Takenori Tomaru, Tomotaro Hoshika, Toshiki Fukushima
PloS one 15巻2号e0229573-頁 2020年
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15. |
Four-types of IIT-induced group integrity of Plecoglossus altivelis
(査読有り)
Takayuki Niizato, Kotaro Sakamoto, Yoh-ichi Mototake, Hisashi Murakami, Yuta Nishiyama, Toshiki Fukushima
Entropy 22巻7号726頁 2020年
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16. |
Data-based selection of creep constitutive models for high-Cr heat-resistant steel
(査読有り)
IZUNO, Hitoshi, Demura, Masahiko, TABUCHI, Masaaki, Mototake, Yoh-ichi, Okada, Masato
Science and Technology of Advanced Materials 21巻1号219-228頁 2020年 |
17. |
Towards a Geometrical Understanding of Physical Phenomena via Extraction of Data Manifolds using Generative Models
(査読有り)
Kotaro Sakamoto, Yuichiro Mori, Yoh-ichi Mototake
Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications 2020年 |
18. |
Topological Data Analysis for microdomain patternsof Block Copolymer
(査読有り)
Yoh-ichi Mototake, Sadato Yamanaka, Takeshi Aoyagi, Takaaki Ohnishi, Kenji Fukumizu
Proceedings of the 2020 International Symposium on Nonlinear Theory and its Applications 2020年 |
19. |
Revealing the existence of the ontological commitment in fish schools
(査読有り)
Takayuki Niizato, Kotaro Sakamoto, Yoh-ichi Mototake, Hisashi Murakami, Takenori Tomaru, Tomotaro Hoshika, Toshiki Fukushima
Artif Life Robotics 25巻633-633–642頁 2020年
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20. |
Universal Framework of Bayesian Creep Model Selection for Steel
(査読有り)
Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada
Materials Research Meeting 2019 2019年12月 |
21. |
Universal Framework of Bayesian Creep Model Selection for Steel
(査読有り)
Yoh-ichi Mototake, Hitoshi Izuno, Kenji Nagata, Masahiko Demura, Masato Okada
International Conference on Computational & Experimental Engineering and Sciences 2019年3月 |
22. |
Descriptor Extraction on Inherent Creep Strength of Carbon Steels by Exhaustive Search
(査読有り)
Junya Sakurai, Junya Inoue, Masahiko Demura, Yoichi Mototake, Masato Okada, Masayoshi Yamazaki
International Conference on Computational & Experimental Engineering and Sciences 2019年 |
23. |
Creep Model Selection for Grade 91 Steel Using Data Scientific Method
(査読有り)
Hitoshi Izuno, Masahiko Demura, Masaaki Tabuchi, Yohichi Mototake, Masato Okada
International Conference on Computational & Experimental Engineering and Sciences 2019年 |
24. |
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
(査読有り)
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年 |
25. |
Heap Paradox in Fish Schools
(査読有り)
Takayuki Niizato, Kotaro Sakamoto, Yoh-Ichi Mototake, Hisashi Murakami, Yuta Nishiyama, Toshiki Fukushima
SWARM2019 2019年 |
26. |
Bayesian Spectral Deconvolution Based on Poisson Distribution: Bayesian Measurement and Virtual Measurement Analytics (VMA)
(査読有り)
Kenji Nagata, Yoh-ichi Mototake, Rei Muraoka, Takehiko Sasaki, Masato Okada
Journal of the Physical Society of Japan 88巻4号044003頁 2019年
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27. |
Conservation Law Estimation by Extracting the Symmetry of a Dynamical System Using a DNN
(査読有り)
Yoh-ichi Mototake
NeurIPS2019 Workshop on Machine Learning and the Physical Sciences(ML4PS) 2019年 |
28. |
Semi-flat minima and saddle points by embedding neural networks to overparameterization
(査読有り)
Kenji Fukumizu, Shoichiro Yamaguch, Yoh-ichi Mototake, Mirai Tanaka
Advances in Neural Information Processing Systems (NeurIPS) 2019年 |
29. |
Bayesian Hamiltonian Selection in X-ray Photoelectron Spectroscopy
(査読有り)
Yoh-ichi Mototake, Masaichiro Mizumaki, Ichiro Akai, Masato Okada
Journal of the Physical Society of Japan 88巻3号 2019年
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30. |
Spectral deconvolution through bayesian LARS-OLS
(査読有り)
Yoh-ichi Mototake, Yasuhiko Igarashi, Hikaru Takenaka, Kenji Nagata, Masato Okada
Journal of the Physical Society of Japan 87巻11号 2018年 |
31. |
Life as an emergent phenomenon: studies from a large-scale boid simulation and web data
(査読有り)
Takashi Ikegami, Yoh-ichi Mototake, Shintaro Kobori, Mizuki Oka, Yasuhiro Hashimoto
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES 375巻2109号 2017年12月
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32. |
Revisiting Classification of Large Scale Flocking
(査読有り)
Norihiro Maruyama, Yasuhiro Hashimoto, Yhoichi Mototake, Daichi Saito, Takashi Ikegami
The 2nd International Symposium on Swarm Behavior and Bio-Inspired Robotics 2017年 |
33. |
Creating an in-group relation between humans and agents
(査読有り)
Yoh Ichi Mototake, Haruaki Fukuda, Kazuhiro Ueda
Transactions of the Japanese Society for Artificial Intelligence 31巻6号AI30-J_1-10-頁 2016年
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34. |
The dynamics of deep neural networks
(査読有り)
Yhoichi Mototake, Takashi Ikegami
the Twentieth International Symposium on Artificial Life and Robotics 2015年 |
35. |
A Simulation Study of Large Scale Swarms
(査読有り)
Yhoichi Mototake, Takashi Ikegami
The 1st International Symposium on Swarm Behavior and Bio-Inspired Robotics 2015 2015年 |