出版物

書籍

多変量解析（統計的機械学習）によるスペクトルイメージング解析
志賀元紀, 青柳里果
「図説表面分析ハンドブック」（日本表面真空学会編）, p.536-543, 朝倉書店（2021年）
High Spatial Resolution Hyperspectral Imaging with Machine-Learning Techniques
Motoki Shiga, Shunsuke Muto
Nanoinformatics (Editor Prof. Isao Tanaka), Ch. 9（p.179-203）, Springer, 2018.
[Open Access]
脳神経システム解析のための数理アルゴリズム
横田康成，志賀元紀
「ニューロインフォマティクス」（甘利俊一監修，臼井支朗編）, 分担執筆, 7.3節（p.266-277）, オーム社, 2006. [出版社のページ]

雑誌論文

Ring compaction as a mechanism of densification in amorphous silica
Philip S. Salmon, Anita Zeidler, Motoki Shiga, Yohei Onodera, Shinji Kohara,
Physical Review B, 2023. (Accepted)
Local structure analysis of disordered materials via contrast variation in scanning transmission electron microscopy
Koji Kimoto, Motoki Shiga, Shinji Kohara, Jun Kikkawa, Ovidiu Cretu, Yohei Onodera, Kazuo Ishizuka,
AIP Advances, 12, 095219, 2022.
A Generalized framework of multi-fidelity max-value entropy search through joint entropy
Shion Takeno, Hitoshi Fukuoka, Yuki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, and Masayuki Karasuyama
Neural Computation, 34 (10), 2145–2203, 2022.
Relationship between diffraction peak, network topology, and amorphous-forming ability in silicon and silica
Shinji Kohara, Motoki Shiga, Yohei Onodera, Hirokazu Masai, Akihiko Hirata, Motohiko Murakami, Tetsuya Morishita, Koji Kimura, Kouichi Hayashi
Scientific Reports, 11, 22180, 2021.
Accelerated discovery of proton-conducting perovskite oxide by capturing physicochemical fundamentals of hydration
Jyunji Hyodo, Kota Tsujikawa, Motoki Shiga, Yuji Okuyama, Yoshihiro Yamazaki
ACS Energy Letters, 6, 2985-2992, 2021.
機械学習を用いたペロブスカイト酸化物におけるプロトン濃度の予測精度の評価
辻川皓太, 兵頭潤次, 志賀元紀, 奥山勇治, 山崎仁丈
燃料電池, 20, 75-86, 2021.
Structure and properties of densified silica glass: characterizing the order within disorder
Yohei Onodera, Shinji Kohara, Philip S. Salmon, Akihiko Hirata, Norimasa Nishiyama, Suguru Kitani, Anita Zeidler, Motoki Shiga, Atsunobu Masuno, Hiroyuki Inoue, Shuta Tahara, Annalisa Polidori, Henry E. Fischer, Tatsuya Mori, Seiji Kojima, Hitoshi Kawaji, Alexander I. Kolesnikov, Matthew B. Stone, Matthew G. Tucker, Marshall T. McDonnell, Alex C. Hannon, Yasuaki Hiraoka, Ippei Obayashi, Takenobu Nakamura, Jaakko Akola, Yasuhiro Fujii, Koji Ohara, Takashi Taniguchi, Osami Sakata
NPG Asia Materials , 12, 85, 2020.
Cost-effective search for lower-error region in material parameter space using multifidelity Gaussian process modeling
Shion Takeno, Yuhki Tsukada, Hitoshi Fukuoka, Toshiyuki Koyama, Motoki Shiga, Masayuki Karasuyama
Physical Review Materials, 4, 083802, 2020.
Application of machine learning techniques to electron microscopic/spectroscopic image data analysis
Shunsuke Muto, Motoki Shiga
Microscopy, 69 (2), 110-122, 2020.
Understanding diffraction patterns of glassy, liquid and amorphous materials via persistent homology analyses
Yohei Onodera, Shinji Kohara, Shuta Tahara, Atsunobu Masuno, Hiroyuki Inoue, Motoki Shiga, Akihiko Hirata, Koichi Tsuchiya, Yasuaki Hiraoka, Ippei Obayashi, Koji Ohara, Akitoshi Mizuno, Osami Sakata
Journal of the Ceramic Society of Japan, Vol. 127, No.12, 853-863, 2019. (Cover)
Estimation of material parameters based on precipitate shape: efficient identification of low-error region with Gaussian process modeling
Yuhki Tsukada, Shion Takeno, Masayuki Karasuyama, Hitoshi Fukuoka, Motoki Shiga, Toshiyuki Koyama
Scientific Reports, 9, 15794, 2019.
Non-negative matrix factorization and its extensions for spectral image data analysis
Motoki Shiga, Shunsuke Muto
e-Journal of Surface Science and Nanotechnology, 17, 148-154, 2019.
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
Michael Patrick Menden, Dennis Wang, Yuanfang Guan, Michael Mason, Bence Szalai, Krishna C Bulusu, Thomas Yu, Jaewoo Kang, Minji Jeon, Russ Wolfinger, Tin Nguyen, Mikhail Zaslavskiy, AstraZeneca-Sanger Drug Combination DREAM Consortium, In Sock Jang, Zara Ghazoui, Mehmet Eren Ahsen, Robert Vogel, Elias Chaibub Neto, Thea Norman, Eric KY Tang, Mathew J Garnett, Giovanni Di Veroli, Stephen Fawell, Gustavo Stolovitzky, Justin Guinney, Jonathan R Dry, Julio Saez-Rodriguez
Nature Communications, Vol.10, 2674, 2019.
多変量解析を利用したTOF-SIMSイメージデータフュージョンとスパースモデリングおよび機械学習によるTOF-SIMSスペクトル解析
石倉航, 高橋一真, 山㟁崇之, 青木弾, 福島和彦, 志賀元紀, 青柳里果
Journal of Surface Analysis, Vol. 25, No.2, 103-114, 2018.
A Crowdsourced Analysis to Identify ab Initio Molecular Signatures Predictive of Susceptibility to Viral Infection
Slim Fourati, Aarthi Talla, Mehrad Mahmoudian, Joshua G Burkhart, Riku Klen, Ricardo Henao, Zafer Aydin, Ka Yee Yeung, Mehmet Eren Ahsen, Reem Almugbel, Samad Jahandideh, Xiao Liang, Torbjorn E.M. Nordling, Motoki Shiga, Ana Stanescu, Robert Vogel, The Respiratory Viral DREAM Challenge Consortium, Gaurav Pandey, Christopher Chiu, Micah T McClain, Chris W Woods, Geoffrey S Ginsburg, Laura L Elo, Ephraim L Tsalik, Lara M Mangravite, Solveig K Sieberts
Nature Communications, Vol. 9, 4418, 2018.
Informatics-Aided Raman Microscopy for Nanometric 3D Stress Characterization
Hongxin Wang, Han Zhang , Bo Da, Motoki Shiga, Hideaki Kitazawa, Daisuke Fujita
Journal of Physical Chemistry C, Vol.122, No.13, 7187-7193, 2018.
Exploring a Potential Energy Surface by Machine Learning for Characterizing Atomic Transport
Kenta Kanamori, Kazuaki Toyoura, Junya Honda, Atsuto Seko, Masayuki Karasuyama, Kazuki Shitara, Motoki Shiga, Akihide Kuwabara, Ichiro Takeuchi
Physical Review B, 97, 125124, 2018.
Time Variations of the Radial Velocity of H2O Masers in the Semi-Regular Variable R CRT
Hiroshi Sudou*, Motoki Shiga*, Toshihiro Omodaka, Chihiro Nakai, Kazuki Ueda and Hiroshi Takaba (*第1著者: SudouとShiga)
Journal of the Korean Astronomical Society, Vol.50, No.6, 157-165, 2017.
Prediction of Overall Survival for Patients with Metastatic Castration-Resistant Prostate Cancer: Development of a Prognostic Model through a Crowdsourced Challenge with Open Clinical Trial Data
Justin Guinney, Tao Wang, Teemu D Laajala, Kimberly Kanigel Winner, J Christopher Bare, Elias Chaibub Neto, Suleiman A Khan, Gopal Peddinti, Antti Airola, Tapio Pahikkala, Tuomas Mirtti, Thomas Yu, Brian M Bot, Liji Shen, Kald Abdallah, Thea Norman, Stephen Friend, Gustavo Stolovitzky, Howard Soule, Christopher J Sweeney, Charles J Ryan, Howard I Scher, Oliver Sartor, Yang Xie, Tero Aittokallio, Fang Liz Zhou, James C Costello, the Prostate Cancer Challenge DREAM Community
The Lancet Oncology, 18(1), 132–142, 2017.
Two-step Feature Selection for Predicting Survival Time of Patients with Metastatic Castrate Resistant Prostate Cancer
Motoki Shiga
F1000Research, vol. 5, 2678, 2016.
Matrix Factorization for Automatic Chemical Mapping from Electron Microscopic Spectral Imaging Datasets
Motoki Shiga, Shunsuke Muto, Kazuyoshi Tatsumi, Koji Tsuda
Transactions of the Materials Research Society of Japan, vol. 41, no. 4, p. 333-336, 2016.
Sparse Modeling of EELS and EDX Spectral Imaging Data by Nonnegative Matrix Factorization
Motoki Shiga, Kazuyoshi Tatsumi, Shunsuke Muto, Koji Tsuda, Yuta Yamamoto, Toshiyuki Mori, Takayoshi Tanji
Ultramicroscopy, 170, p.43-59, 2016.
A machine learning-based selective sampling procedure for identifying the low energy region in a potential energy surface: a case study on proton conduction in oxides
Kazuaki Toyoura, Daisuke Hirano, Atsuto Seko, Motoki Shiga, Akihide Kuwabara, Masayuki Karasuyama, Kazuki Shitara, Ichiro Takeuchi
Physical Review B, vol. 93, issue 5, 054112, 2016.
Direct Conditional Probability Density Estimation with Sparse Feature Selection
Motoki Shiga, Voot Tangkaratt, Masashi Sugiyama
Machine Learning, vol.100, no.2, pp.161-182, 2015. [コード]
Non-negative Matrix Factorization with Auxiliary Information on Overlapping Groups
Motoki Shiga, Hiroshi Mamitsuka
IEEE Transactions on Knowledge and Data Engineering, vol.27, no.6, pp.1615-1628, 2015.
Detecting Differentially Coexpressed Genes from Labeled Expression Data: A Brief Review
Mitsunori Kayano, Motoki Shiga, Hiroshi Mamitsuka
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 11(1), p.154-167, 2014. [DOI:10.1109/TCBB.2013.2297921]
化学構造の高速データマイニングのための特徴ベクトル TFS の圧縮法
志賀元紀, 高橋由雅
Journal of Computer Chemistry, Japan, vol.11, no.2, pp.104-111, 2012. (IF=NaN)
A Variational Bayesian Framework for Clustering with Multiple Graphs
Motoki Shiga, Hiroshi Mamitsuka
IEEE Transactions on Knowledge and Data Engineering, vol.24, no.4, pp.577-590, 2012. [Link] (IF=1.892)
Efficient Semi-Supervised Learning on Locally Informative Multiple Graphs
Motoki Shiga, Hiroshi Mamitsuka
Pattern Recognition, vol. 45, issue 3, pp.1035-1049, 2012. [Link] (IF=2.632)
Genome-wide Integration on Transcription Factors, Histone Acetylation and Gene Expression Reveals Genes Co-regulated by Histone Modification Patterns
Yayoi Natsume-Kitatani, Motoki Shiga, Hiroshi Mamitsuka
PLoS One, 6(7), e22281, 2011. [Link](IF=4.049)
ROS-DET: Robust Detector of Switching Mechanisms in Gene Expression
Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka
Nucleic Acids Research, 39(11), e74, 2011. [Link](IF=8.026)
Clustering Genes with Expression and Beyond
Motoki Shiga, Hiroshi Mamitsuka
WIREs Data Mining and Knowledge Discovery, Invited paper, 1(6), p.496-511, 2011. [DOI:10.1002/widm.41](IF=創刊年のため測定不能)
A Spectral Approach to Clustering Numerical Vectors as Nodes in a Network
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
Pattern Recognition, Vol.44, issue 2, pp.236-251, 2011. [Link](IF=2.292)
On the Performance of Methods for Finding a Switching Mechanism in Gene Expression
Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka
Genome Informatics, Vol.24, pp.69-83, 2010. [Link]
(Proceedings of the 10th Annual International Workshop on Bioinformatics and Systems Biology IBSB2010)) (IF=NaN)
Efficiently Finding Genome-wide Three-way Gene Interactions from Transcript- and Genotype-Data
Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka
Bioinformatics, Vol.25, pp.2735-2743, 2009. [PubMed](IF=4.926)
Annotating Gene Functions with Integrative Spectral Clustering on Microarray Expressions and Sequences
Limin Li, Motoki Shiga, Wai-ki Ching, Hiroshi Mamitsuka
Genome Informatics, Vol.22, pp.95-120, 2009. [Link]
(Proceedings of the 9th Annual International Workshop on Bioinformatics and Systems Biology (IBSB2009)) (IF=NaN)
Upper Bound for Variational Free Energy of Bayesian Networks
Kazuho Watanabe, Motoki Shiga, Sumio Watanabe
Machine Learning, Vol.75, issue 2, pp.199-215, 2009. [Link](IF=1.663)
多様なゲノムデータの統合的クラスタリング解析
志賀元紀, 瀧川一学, 馬見塚拓,
生物物理, 理論/実験技術, Vol.48, pp.190-194, 2008. [Link] (IF=NaN)
Mining Significant Tree Patterns in Carbohydrate Sugar Chains
Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka
Bioinformatics, Vol.24, i167-i173, 2008. [PubMed]
(Proceedings of the 7th European Conference on Computational Biology (ECCB2008)) (IF=4.328)
Annotating Gene Function by Combining Expression Data with a Modular Gene Network
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
Bioinformatics, Vol.23, i468-i478, 2007. [PubMed]
(Proceedings of the 15th Annual International Conference on Intelligent Systems for Molecular Biology & 6th European Conference on Computational Biology
(ISMB/ECCB2007))(IF=5.039)
推定を独立な標本から繰り返す場合に最適なエントロピー推定量
志賀元紀, 横田康成,
電気学会論文誌部門誌C, 研究開発レター, Vol.125-C, No.12, pp.1912-1913, 2005. (IF=NaN)
バイアス誤差の2乗平均を任意の値に制約する条件下で平均2乗誤差を最小化するエントロピー推定量
志賀元紀, 横田康成,
電子情報通信学会論文誌A, Vol.J88-A, No.4, pp.519-527, 2005. (IF=NaN)
Effect of Time Division on Estimation Accuracy in Frequency Domain ICA
Yasunari Yokota, Hideaki Iwata, Motoki Shiga
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol.E87-A, No.12, pp.3424-3428, 2004. (IF=0.318)
平均2乗誤差を改善するエントロピー推定量
横田康成, 志賀元紀,
電子情報通信学会論文誌A, Vol.J86-A, No.9, pp.936-944, 2003. (IF=NaN)

国際会議・国際ワークショップ論文

Multi-fidelity Bayesian Optimization with Max-value Entropy Search and its Parallelization
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama, Proc. of The 37th International Conference on Machine Learning (ICML 2020), to appear (Acceptance rate 22%).
Mining Physical/Chemical Properties from Nano-Scale Areas Using STEM Spectroscopic Methods and Informatics Techniques
Shunsuke Muto, Jakob Spiegelberg, Motoki Shiga, Masahiro Ohtsuka, Jan Rusz
Proceedings on the 10th Pacific Rim International Conference on Advanced Materials and Processing, pp.720-729, Xi'an, China, August 2019.
Direct Conditional Probability Density Estimation with Sparse Feature Selection
Motoki Shiga, Voot Tangkaratt, Masashi Sugiyama
Proceedings on European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD2015), Porto, Portugal, September 2015.
Variational Bayes Co-clustering with Auxiliary Information
Motoki Shiga, Hiroshi Mamitsuka
Proceedings on the 4th MultiClust Workshop on Multiple Clusterings, Multi-view Data, and Multi-source Knowledge-driven Clustering (MultiClust2013), pp. 1-4, Chicago, Illinois, USA, August 2013.
Variational Bayes Learning over Multiple Graphs
Motoki Shiga, Hiroshi Mamitsuka
Proceedings of the IEEE International Workshop on Machine Learning for Signal Processing 2010(MLSP2010), pp. 166-171, Kittila, Finland, August 2010. (採択率30% (=36/122))
On the Performance of Methods for Finding a Switching Mechanism in Gene Expression
Mitsunori Kayano, Ichigaku Takigawa, Motoki Shiga, Koji Tsuda, Hiroshi Mamitsuka
Proceedings of the 10th Annual International Workshop on Bioinformatics and Systems Biology (IBSB2010), Kyoto, Japan, July 2010. (Genome Informatics, Vol.24, pp.69-83, 2010. [Link])
Annotating Gene Functions with Integrative Spectral Clustering on Microarray Expressions and Sequences
Limin Li, Motoki Shiga, Wai-ki Ching, Hiroshi Mamitsuka
Proceedings of the 9th Annual International Workshop on Bioinformatics and Systems Biology (IBSB2009), Boston, MA, USA, July 2009. (Genome Informatics, Vol.22, pp.95-120, 2009. [Link])
Mining Significant Tree Patterns in Carbohydrate Sugar Chains
Kosuke Hashimoto, Ichigaku Takigawa, Motoki Shiga, Minoru Kanehisa, Hiroshi Mamitsuka
Proceedings of the 7th European Conference on Computational Biology (ECCB2008) Sardinia, Italy, September 2008. (Bioinformatics, Vol. 24, i167-i173, 2008 [PubMed])(採択率19% (=36/186) )
A Spectral Clustering Approach to Optimally Combining Numerical Vectors with a Modular Network
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
Proceedings of the 13th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD2007), pp.647-656, San Jose, CA, USA, August 2007.[ACM] (採択率19% (=111/573))
Annotating Gene Function by Combining Expression Data with a Modular Gene Network
Motoki Shiga, Ichigaku Takigawa, Hiroshi Mamitsuka
Proceedings of the 15th Annual International Conference on Intelligent Systems for Molecular Biology & 6th European Conference on Computational Biology (ISMB/ECCB2007)), Wien, Austria, July 2007. (Bioinformatics, Vol.23, i468-i478, 2007 [PubMed]) (採択率15% (=66/418))
Upper Bounds for Variational Stochastic Complexities of Bayesian Networks
Kazuho Watanabe, Motoki Shiga, Sumio Watanabe
Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL2006), Burgos, Spain, September 2006. (Lecture Notes in Computer Science (LNCS), vol. 4424, pp.139-146, 2006)
An Optimal Entropy Estimator for Discrete Random Variables
Motoki Shiga, Yasunari Yokota
Proceedings of the 18th International Joint Conference on Neural Networks (IJCNN2005), pp.1280-1285, Montreal, Canada, July 2005.
本発表に関する旅費を井上科学振興財団より補助していただきました。
Error Analysis of Entropy Estimator for A Memory-less Information Source
Motoki Shiga, Yasunari Yokota
Proceedings of the International Workshop on Nonlinear Signal and Image Processing 2005 (NSIP2005), pp.99-104, Sapporo, Japan, May 2005

総説・レビュー論文

低カウントのスペクトラムイメージ解析のための機械学習法
志賀元紀, 武藤俊介
日本顕微鏡学会「顕微鏡」, Vol.57, No. 2, 65-69, 2022.
次元削減法とそのスペクトル解析への応用
武藤俊介, 志賀元紀
日本鉄鋼協会「ふぇらむ」, Vol.26, No. 7, 434-442, 2021.
スペクトラムイメージデータのノイズ処理と信号抽出の最近の進展
武藤俊介, 志賀元紀
日本顕微鏡学会「顕微鏡」, Vol.55, No. 2, 60-64, 2020.
パーシステントホモロジーを用いた非晶質物質の回折パターンの理解と二体相関に潜んだトポロジーの抽出
小原真司, 坂田修身, 小野寺陽平, 大林一平, 志賀元紀, 平田秋彦, 平岡裕章
日本結晶学会誌, Vol.62, No.1, 43-50, 2020.
ガラスの二体相関に隠れたトポロジーの抽出
小原真司, 小野寺陽平, 大林一平, 志賀元紀, 平田秋彦, 平岡裕章, 坂田修身,
New Glass, Vol.35, No.129, 24-30, 2020.
統計的機械学習に基づく低カウントのスペクトルイメージ解析
志賀元紀, 武藤俊介
電気化学学会「電気化学」, Vol.88, No. 1, 42-46, 2020.
スペクトル解析のための統計的機械学習
志賀元紀
金属学会誌「まてりあ」, 58(1), p.23-28, 2019.
スペクトラムイメージ解析のためのインフォマティクス技術
志賀元紀
化学工業, 特集：マテリアルズ・インフォマティクスの未来展望, 69(1), p.33-38, 2018.
スペクトルイメージデータ解析への統計・情報処理
武藤俊介, 志賀元紀
日本表面科学会「表面科学」, 37(12), p.610-615, 2016.
ナノ電子顕微分光における情報処理技法の応用
武藤俊介, 志賀元紀, 巽一厳, 津田宏治
日本セラミックス協会「セラミックス」, 50(7), p.527-530, 2015.

プレプリント

Ring-originated anisotropy of local structure ordering in amorphous and crystalline silicon dioxide
Motoki Shiga, Akihiko Hirata, Yohei Onodera, Hirokazu Masai,
arXiv:2209.12116, 2022. [preprint]
Noise robust automatic charge state recognition in quantum dots by machine learning and pre-processing, and visual explanations of the model with Grad-CAM
Yui Muto, Takumi Nakaso, Takumi Aizawa, Motoya Shinozaki, Takahito Kitada, Takashi Nakajima, Matthieu R. Delbecq, Jun Yoneda, Kenta Takeda, Akito Noiri, Arne Ludwig, Andreas D. Wieck, Seigo Tarucha, Atsunori Kanemura, Motoki Shiga, Tomohiro Otsuka
arXiv:2210.15070, 2022. [preprint]
Multi-fidelity Bayesian Optimization with Max-value Entropy Search
Shion Takeno, Hitoshi Fukuoka, Yuhki Tsukada, Toshiyuki Koyama, Motoki Shiga, Ichiro Takeuchi, Masayuki Karasuyama
arXiv:1901.08275, 2019.