Publications

Yota Fukui, Kosuke Minami, Kota Shiba, Genki Yoshikawa, Koji Tsuda, Ryo Tamura (2024). Automated odor-blending with one-pot Bayesian optimization. Digital Discovery.

DOI

Masato Sumita, Hisanao Takahashi, Tomoya Sugita, Koji Tsuda (2024). Theoretical Insight into the Origin of Dielectric and Magnetoelectric FeCo Alloy–Metal Fluoride Insulators. Journal of Physical Chemistry C, 128, 1386-1392.

DOI

Andrejs Tucs, Tomoyuki Ito, Yoichi Kurumida, Sakiya Kawada, Hikaru Nakazawa, Yutaka Saito, Mitsuo Umetsu, Koji Tsuda (2024). Extensive antibody search with whole spectrum black-box optimization. Scientific Reports, 14, 552.

DOI

Seoin Back, Alan Aspuru-Guzik, Michele Ceriotti, Ganna Grynova, Bartosz Andrzej Grzybowski, Geun Ho Gu, Jason E Hein, Kedar Hippalgaonkar, Rodrigo Hormazabal, Yousung Jung, Seonah Kim, Woo Youn Kim, Mohamed Moosavi, Juhwan Noh, Changyoung Park, Joshua Schrier, Philipp Schwaller, Koji Tsuda, Tejs Vegge, Anatole von Lilienfeld, Aron Walsh (2024). Accelerated Chemical Science with AI. Digital Discovery, 3, 23-33.

DOI

Tien-Sinh Vu, Minh-Quyet Ha, Duong-Nguyen Nguyen, Viet-Cuong Nguyen, Yukihiro Abe, Truyen Tran, Huan Tran, Hiori Kino, Takashi Miyake, Koji Tsuda, Hieu-Chi Dam (2023). Towards understanding structure–property relations in materials with interpretable deep learning. npj Computational Materials, 9, 215.

DOI

Takumi Yoshida, Hiroyuki Hanada, Kazuya Nakagawa, Kouichi Taji, Koji Tsuda, Ichiro Takeuchi (2023). Efficient model selection for predictive pattern mining model by safe pattern pruning. Patterns, 4, 100890.

DOI

Weilin Yuan, Yusuke Hibi, Ryo Tamura, Masato Sumita, Yasuyuki Nakamura, Masanobu Naito, Koji Tsuda (2023). Revealing factors influencing polymer degradation with rank-based machine learning. Patterns, 4, 100846.

DOI

Kei Terayama, Yamato Osaki, Takehiro Fujita, Ryo Tamura, Masanobu Naito, Koji Tsuda, Toru Matsui, Masato Sumita (2023). Koopmans’ Theorem-Compliant Long-Range Corrected (KTLC) Density Functional Mediated by Black-Box Optimization and Data-Driven Prediction for Organic Molecules. Journal of Chemical Theory and Computation, 19, 6770-6781.

DOI

Ryo Tamura, Kei Terayama, Masato Sumita, Koji Tsuda (2023). Ranking Pareto optimal solutions based on projection free energy. Physical Review Materials, 7, 093804.

DOI

Haishan Zhang, Dai Hai Nguyen, Koji Tsuda (2023). Differentiable optimization layers enhance GNN‑based mitosis detection. Scientific Reports, 13, 14306.

DOI

Jiawen Li, Masato Sumita, Ryo Tamura, Koji Tsuda (2023). Interpretable Fragment-Based Molecule Design with Self-Learning Entropic Population Annealing. Advanced Intelligent Systems, 5, 2300189.

DOI

Shoichi Ishida, Tanuj Aasawat, Masato Sumita, Michio Katouda, Tatsuya Yoshizawa, Kazuki Yoshizoe, Koji Tsuda, Kei Terayama (2023). ChemTSv2: Functional molecular design using de novo molecule generator. WIREs Computational Molecular Science, e1680.

DOI

Chao Huang, Diptesh Das, Koji Tsuda (2023). Feature Importance Measurement based on Decision Tree Sampling. 3rd Workshop on Interpretable Machine Learning in Healthcare.

PDF

Ryo Tamura, Koji Tsuda, Shoichi Matsuda (2023). NIMS-OS: an automation software to implement a closed loop between artificial intelligence and robotic experiments in materials science. STAM Methods, 3, 2232297.

DOI

Zetian Mao, Yoshiki Matsuda, Ryo Tamura, Koji Tsuda (2023). Chemical design with GPU-based Ising machines. Digital Discovery, 2, 1098-1103.

DOI

Andrejs Tucs, Francois Berenger, Akiko Yumoto, Ryo Tamura, Takanori Uzawa, Koji Tsuda (2023). Quantum Annealing Designs Nonhemolytic Antimicrobial Peptides in a Discrete Latent Space. ACS Medicinal Chemistry Letters, 14, 577-582.

DOI

Francois Berenger, Koji Tsuda (2023). 3D-Sensitive Encoding of Pharmacophore Features. Journal of Chemical Information and Modeling, 63, 2360-2369.

DOI

Masaya Hagai, Mahito Sugiyama, Koji Tsuda, Takeshi Yanai (2023). Artificial neural network encoding of molecular wavefunctions for quantum computing. Digital Discovery, 2, 634-650.

DOI

Dai Hai Nguyen, Koji Tsuda (2023). On A Linear Fused Gromov-Wasserstein Distance For Graph Structured Data. Pattern Recognition, 138, 109351.

DOI

Atsuyuki Nakao, Yu Harabuchi, Satoshi Maeda, Koji Tsuda (2023). Exploring the Quantum Chemical Energy Landscape with GNN-Guided Artificial Force. Journal of Chemical Theory and Computation, 19, 713-717.

DOI

Tomoyuki Ito, Thuy Duong Nguyen, Yutaka Saito, Yoichi Kurumida, Hikaru Nakazawa, Sakiya Kawada, Hafumi Nishi, Koji Tsuda, Tomoshi Kameda, Mitsuo Umetsu (2023). Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning. mAbs, 15, 2168470.

DOI

Yuji Kaiya, Ryo Tamura, Koji Tsuda (2022). Understanding Chemical Processes with Entropic Sampling. Organic Process Research & Development, 26, 3276-3282.

DOI

Ryo Tamura, Masato Sumita, Kei Terayama, Koji Tsuda, Fujio Izumi, Yoshitaka Matsushita (2022). Automatic Rietveld refinement by robotic process automation with RIETAN-FP. STAM Methods, 2, 435-444.

DOI

Masato Sumita, Kei Terayama, Ryo Tamura, Koji Tsuda (2022). QCforever: A Quantum Chemistry Wrapper for Everyone to Use in Black-Box Optimization. Journal of Chemical Information and Modeling, 62, 4427-4434.

DOI

Jessica E. Besaw, Joerg Reichenwallner, Paolo De Guzman, Andrejs Tucs, Anling Kuo, Takefumi Morizumi, Koji Tsuda, Adnan Sljoka, R. J. Dwayne Miller, Oliver P. Ernst (2022). Low pH structure of heliorhodopsin reveals chloride binding site and intramolecular signaling pathway. Scientific Reports, 12, 13955.

DOI

Masaya Kumagai, Yuki Ando, Atsumi Tanaka, Koji Tsuda, Yukari Katsura, Ken Kurosaki (2022). Effects of data bias on machine-learning–based material discovery using experimental property data. STAM Methods, 2, 302-309.

DOI

Yuichi Motoyama, Ryo Tamura, Kazuyoshi Yoshimi, Kei Terayama, Tsuyoshi Ueno, Koji Tsuda (2022). Bayesian optimization package: PHYSBO. Computer Physics Communications, 278, 108405.

DOI

Takehiro Fujita, Kei Terayama, Masato Sumita, Ryo Tamura, Yasuyuki Nakamura, Masanobu Naito, Koji Tsuda (2022). Understanding the evolution of a de novo molecule generator via characteristic functional group monitoring. Science and Technology of Advanced Materials, 23, 352-360.

DOI

Shun Izawa, Koki Kitai, Shu Tanaka, Ryo Tamura, Koji Tsuda (2022). Continuous black-box optimization with an Ising machine and random subspace coding. Physical Review Research, 4, 023062.

DOI

Atsuyuki Nakao, Yu Harabuchi, Satoshi Maeda, Koji Tsuda (2022). Leveraging algorithmic search in quantum chemical reaction path finding. Physical Chemistry Chemical Physics, 24, 10305-10310.

DOI

Jiawen Li, Jinzhe Zhang, Ryo Tamura, Koji Tsuda (2022). Self-learning entropic population annealing for interpretable materials design. Digital Discovery, 1, 295-302.

DOI

Tomoki Yamashita, Hiori Kino, Koji Tsuda, Takashi Miyake, Tamio Oguchi (2022). Hybrid algorithm of Bayesian optimization and evolutionary algorithm in crystal structure prediction. STAM Methods, 2, 67-74.

DOI

Masato Sumita, Kei Terayama, Naoya Suzuki, Shinsuke Ishihara, Ryo Tamura, Mandeep K. Chahal, Daniel T. Payne, Kazuki Yoshizoe, Koji Tsuda (2022). De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning. Science Advances, 8, eabj3906.

DOI

Diptesh Das, Vo Nguyen Le Duy, Hiroyuki Hanada, Koji Tsuda, Ichiro Takeuchi (2022). Fast and More Powerful Selective Inference for Sparse High-Order Interaction Model. 36th AAAI Conference on Artificial Intelligence.

PDF

Dai Hai Nguyen, Koji Tsuda (2022). Generating reaction trees with cascaded variational autoencoders. Journal of Chemical Physics, 156, 044117.

DOI

Nitesh Kumawat, Andrejs Tucs, Soumen Bera, Gennady N. Chuev, Marat Valiev, Marina V. Fedotova, Sergey E. Kruchinin, Koji Tsuda, Adnan Sljoka, Amit Chakraborty (2022). Site Density Functional Theory and Structural Bioinformatics Analysis of the SARS-CoV Spike Protein and hACE2 Complex. Molecules, 27, 799.

DOI

Xiaolin Sun, Ryo Tamura, Masato Sumita, Kenichi Mori, Kei Terayama, Koji Tsuda (2022). Integrating Incompatible Assay Data Sets with Deep Preference Learning. ACS Medicinal Chemistry Letters, 13, 70-75.

DOI

Yutaka Saito, Misaki Oikawa, Takumi Sato, Hikaru Nakazawa, Tomoyuki Ito, Tomoshi Kameda, Koji Tsuda, Mitsuo Umetsu (2021). Machine-Learning-Guided Library Design Cycle for Directed Evolution of Enzymes: The Effects of Training Data Composition on Sequence Space Exploration. ACS Catalysis, 11, 14615-14624.

DOI

Francois Berenger, Koji Tsuda (2021). Molecular generation by Fast Assembly of (Deep)SMILES fragments. Journal of Cheminformatics, 13, 88.

DOI

Kei Terayama, Masato Sumita, Michio Katouda, Koji Tsuda, Yasushi Okuno (2021). Efficient Search for Energetically Favorable Molecular Conformations against Metastable States via Gray-Box Optimization. Journal of Chemical Theory and Computation, 17, 5419-5427.

DOI

Tomoki Yamashita, Shinichi Kanehira, Nobuya Sato, Hiori Kino, Kei Terayama, Hikaru Sawahata, Takumi Sato, Futoshi Utsuno, Koji Tsuda, Takashi Miyake, Tamio Oguchi (2021). CrySPY: a crystal structure prediction tool accelerated by machine learning. STAM Methods, 1, 87-97.

DOI

Hanxiao Xu, Koki Kitai, Kosuke Minami, Makito Nakatsu, Genki Yoshikawa, Koji Tsuda, Kota Shiba, Ryo Tamura (2021). Determination of quasi-primary odors by endpoint detection. Scientific Reports, 11, 12070.

DOI

Yucheng Zhang, Jinzhe Zhang, Kuniko Suzuki, Masato Sumita, Kei Terayama, Jiawen Li, Zetian Mao, Koji Tsuda, Yuji Suzuki (2021). Discovery of polymer electret material via de novo molecule generation and functional group enrichment analysis. Applied Physics Letters, 118, 223904.

DOI

Yoshiki Takagiwa, Zhufeng Hou, Koji Tsuda, Teruyuki Ikeda, Hiroyasu Kojima (2021). Fe−Al−Si Thermoelectric (FAST) Materials and Modules: Diffusion Couple and Machine-Learning-Assisted Materials Development. ACS Applied Materials & Interfaces, 13, 53346-53354.

DOI

Duy Phuoc Tran, Seiichi Tada, Akiko Yumoto, Yoshihiro Ito, Takanori Uzawa, Koji Tsuda (2021). Using molecular dynamics simulations to prioritize and understand AI-generated cell penetrating peptides. Scientific Reports, 11, 10630.

DOI

Takuya Okamoto, David duVerle, Katsuyuki Yaginuma, Yasuko Natsume, Hitomi Yamanaka, Daisuke Kusama, Mayuko Fukuda, Mayuko Yamamoto, Fanny Perraudeau, Upasna Srivastava, Yukie Kashima, Ayako Suzuki, Yuuta Kuze, Yu Takahashi, Masashi Ueno, Yoshiharu Sakai, Tetsuo Noda, Koji Tsuda, Yutaka Suzuki, Satoshi Nagayama, Ryoji Yao (2021). Comparative Analysis of Patient-Matched PDOs Revealed a Reduction in OLFM4-Associated Clusters in Metastatic Lesions in Colorectal Cancer. Stem Cell Reports, 16, 954-967.

DOI

Kei Terayama, Masato Sumita, Ryo Tamura, Koji Tsuda (2021). Black-Box Optimization for Automated Discovery. Accounts of Chemical Research, 54, 1334-1346.

DOI

Zhufeng Hou, Yoshiki Takagiwa, Yoshikazu Shinohara, Yibin Xu, Koji Tsuda (2021). First-principles study of electronic structures and elasticity of Al2Fe3Si3. Journal of Physics: Condensed Matter, 33, 195501.

DOI

Naoto Ienaga, Kentaro Higuchi, Toshinori Takashi, Koichiro Gen, Koji Tsuda, Kei Terayama (2021). Vision-based egg quality prediction in Pacific bluefin tuna (Thunnus orientalis) by deep neural network. Scientific Reports, 11, 6.

DOI

I. Ohkubo, Z. Hou, J.N. Lee, T. Aizawa, M. Lippmaa, T. Chikyow, Koji Tsuda, T. Mori (2021). Realization of closed-loop optimization of epitaxial titanium nitride thin-film growth via machine learning. Materials Today Physics, 16, 100296.

DOI

Ryo Tamura, Toshio Osada, Kazumi Minagawa, Takuma Kohata, Masashi Hirosawa, Koji Tsuda, Kyoko Kawagishi (2021). Machine learning-driven optimization in powder manufacturing of Ni-Co based superalloy. Materials and Design, 198, 109290.

DOI

Yuta Takahashi, Kazuki Yoshizoe, Masao Ueki, Gen Tamiya, Yu Zhiqian, Yusuke Utsumi, Atsushi Sakuma, Koji Tsuda, Atsushi Hozawa, Ichiro Tsuji, Hiroaki Tomita (2020). Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms. Scientific Reports, 10, 21726.

DOI

Ryosuke Shibukawa, Shoichi Ishida, Kazuki Yoshizoe, Kunihiro Wasa, Kyosei Takasu, Yasushi Okuno, Kei Terayama, Koji Tsuda (2020). CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration. Journal of Cheminformatics, 12, 52.

DOI

Andrejs Tucs, Duy Phuoc Tran, Akiko Yumoto, Yoshihiro Ito, Takanori Uzawa, Koji Tsuda (2020). Generating Ampicillin-Level Antimicrobial Peptides with Activity-Aware Generative Adversarial Networks. ACS Omega, 5, 22847-22851.

DOI

Jinzhe Zhang, Kei Terayama, Masato Sumita, Kazuki Yoshizoe, Kengo Ito, Jun Kikuchi, Koji Tsuda (2020). NMR-TS: de novo molecule identification from NMR spectra. Science and Technology of Advanced Materials, 21, 552-561.

DOI

Kristof T. Schutt, Stefan Chmiela, O. Anatole von Lilienfeld, Alexandre Tkatchenko, Koji Tsuda, Klaus-Robert Muller (2020). Machine Learning Meets Quantum Physics. Springer Nature.

DOI

Kei Terayama, Masato Sumita, Ryo Tamura, Daniel T. Payne, Mandeep K. Chahal, Shinsuke Ishihara, Koji Tsuda (2020). Pushing property limits in materials discovery via boundless objective-free exploration. Chemical Science, 11, 5959-5968.

DOI

Kenji Homma, Yu Liu, Masato Sumita, Ryo Tamura, Naoki Fushimi, Junichi Iwata, Koji Tsuda, Chioko Kaneta (2020). Optimization of Heterogeneous Ternary Li3PO4-Li3BO3-Li2SO4 Mixture for Li-ion Conductivity by Machine Learning. Journal of Physical Chemistry C, 124, 12865-12870.

DOI arXiv

Peng-Jian Yang, Mahito Sugiyama, Koji Tsuda, Takeshi Yanai (2020). Artificial Neural Networks Applied as Molecular Wave Function Solvers. Journal of Chemical Theory and Computation, 16, 3513-3529.

DOI

Hiromichi Hagihara, Naoto Ienaga, Daiki Enomoto, Shuhei Takahata, Hiroyuki Ishihara, Haruka Noda, Koji Tsuda, Kei Terayama (2020). Computer Vision-Based Approach for Quantifying Occupational Therapists Qualitative Evaluations of Postural Control. Occupational Therapy International, 8542191.

DOI

Xiaolin Sun, Zhufeng Hou, Masato Sumita, Shinsuke Ishihara, Ryo Tamura, Koji Tsuda (2020). Data Integration for Accelerated Materials Design via Preference Learning. New Journal of Physics, 22, 055001.

DOI

Ryo Kanada, Atsushi Tokuhisa, Koji Tsuda, Yasushi Okuno, Kei Terayama (2020). Exploring Successful Parameter Region for Coarse-Grained Simulation of Biomolecules by Bayesian Optimization and Active Learning. Biomolecules, 10, 482.

DOI

Koki Kitai, Jiang Guo, Shenghong Ju, Shu Tanaka, Koji Tsuda, Junichiro Shiomi, Ryo Tamura (2020). Designing metamaterials with quantum annealing and factorization machines. Phys. Rev. Research 2, 013319.

DOI arXiv

Jianbin Qin, Chuan Xiao, Sheng Hu, Jie Zhang, Wei Wang, Yoshiharu Ishikawa, Koji Tsuda, Kunihiko Sadakane (2020). Efficient query autocompletion with edit distance-based error tolerance. The VLDB Journal, 29, 919-943.

DOI

Syusuke Sano, Tadashi Kadowaki, Koji Tsuda, Susumu Kimura (2020). Application of Bayesian Optimization for Pharmaceutical Product Development. Journal of Pharmaceutical Innovation, 15, 333-343.

DOI

Yu Saito, Kento Shin, Kei Terayama, Shaan Desai, Masaru Onga, Yuji Nakagawa, Yuki M. Itahashi, Yoshihiro Iwasa, Makoto Yamada, Koji Tsuda (2019). Deep-learning-based quality filtering of mechanically exfoliated 2D crystals. npj Computational Materials, 5, 124.

DOI

Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda (2019). Legendre decomposition for tensors. Journal of Statistical Mechanics, 124017.

DOI

Kei Terayama, Ai Shibobu, Koji Tsuda, Kazuhiro Takemura, Akio Kitao (2019). evERdock BAI: Machine-learning-guided selection of protein-protein complex structure. Journal of Chemical Physics, 151, 215104.

DOI

Kei Terayama, Koji Tsuda, Ryo Tamura (2019). Efficient recommendation tool of materials by executable file based on machine learning. Japanese Journal of Applied Physics, 58, 9, 098001.

Project DOI

Kento Shin, Duy Phuoc Tran, Kazuhiro Takemura, Akio Kitao, Kei Terayama, Koji Tsuda (2019). Enhancing Biomolecular Sampling with Reinforcement Learning: A Tree Search Molecular Dynamics Simulation Method. ACS Omega, 4, 9, 13853-13862.

Project DOI

Kei Terayama, Kento Shin, Katsunori Mizuno, Koji Tsuda (2019). Integration of sonar and optical camera images using deep neural network for fish monitoring. Aquacultural Engineering, 86, 102000.

Code Dataset DOI

Thaer M. Dieb, Shenghong Ju, Junichiro Shiomi, Koji Tsuda (2019). Monte Carlo tree search for materials design and discovery. MRS Communications, 9, 532-536.

DOI

Zhufeng Hou, Yoshiki Takagiwa, Yoshikazu Shinohara, Yibin Xu, Koji Tsuda (2019). Machine-Learning-Assisted Development and Theoretical Consideration for the Al2Fe3Si3 Thermoelectric Material. ACS Applied Materials and Interfaces, 11, 11545-11554.

DOI

Kei Terayama, Ryo Tamura, Yoshitaro Nose, Hidenori Hiramatsu, Hideo Hosono, Yasushi Okuno, Koji Tsuda (2019). Efficient construction method for phase diagrams using uncertainty sampling. Physical Review Materials, i3, 3, 033802.

DOI

Diptesh Das, Junichi Ito, Tadashi Kadowaki, Koji Tsuda (2019). An interpretable machine learning model for diagnosis of Alzheimer's disease. PeerJ Life & Environment, 7, e6543.

DOI

Atsushi Sakurai, Kyohei Yada, Tetsushi Simomura, Shenghong Ju, Makoto Kashiwagi, Hideyuki Okada, Tadaaki Nagao, Koji Tsuda, Junichiro Shiomi (2019). Ultranarrow-Band Wavelength-Selective Thermal Emission with Aperiodic Multilayered Metamaterials Designed by Bayesian Optimization. ACS Central Science, 5, 2, 319-326.

DOI

Yukari Katsura, Masaya Kumagai, Takushi Kodani, Mitsunori Kaneshige, Yuki Ando, Sakiko Gunji, Yoji Imai, Hideyasu Ouchi, Kazuki Tobita, Kaoru Kimura, Koji Tsuda (2019). Data-driven analysis of electron relaxation times in PbTe-type thermoelectric materials. Science and Technology of Advanced Materials, 20, 511-520.

DOI

Masato Sumita, Ryo Tamura, Kenji Homma, Chioko Kaneta, Koji Tsuda (2019). Li-ion Conductive Li3PO4-Li3BO3-Li2SO4 Mixture: Prevision through Density Functional Molecular Dynamics and Machine Learning. Bulletin of the Chemical Society of Japan, 92, 1100-1106.

DOI

Mahito Sugiyama, Hiroyuki Nakahara, Koji Tsuda (2018). Legendre Decomposition for Tensors. Advances in Neural Information Processing Systems, 31, 8811-8821.

PDF

Mitsugu Araki, Hiroaki Iwata, Biao Ma, Atsuto Fujita, Kei Terayama, Yukari Sagae, Fumie Ono, Koji Tsuda, Narutoshi Kamiya, Yasushi Okuno (2018). Improving the Accuracy of Protein‐Ligand Binding Mode Prediction Using a Molecular Dynamics‐Based Pocket Generation Approach. Journal of computational chemistry, 39, 32, 2679-2689.

DOI

Naruki Yoshikawa, Kei Terayama, Masato Sumita, Teruki Homma, Kenta Oono, Koji Tsuda (2018). Population-based de novo molecule generation using grammatical evolution. Chemistry Letters, 47, 11, 1431-1434.

DOI

Shin Kiyohara, Tomohiro Miyata, Koji Tsuda, Teruyasu Mizoguchi (2018). Data-driven approach for the prediction and interpretation of core-electron loss spectroscopy. Scientific Reports, 8, 13548.

DOI

Kazuki Yoshizoe, Aika Terada, Koji Tsuda (2018). MP-LAMP: Parallel Detection of Statistically Significant Multi-Loci Markers on Cloud Platforms. Bioinformatics, 34, 3047-3049.

DOI

Masato Sumita, Yang Xiufeng, Shinsuke Ishihara, Ryo Tamura, Koji Tsuda (2018). Hunting for Organic Molecules with Artificial Intelligence: Molecules Optimized for Desired Excitation Energies. ACS Central Science, 4, 1126-1133.

DOI

Shuhei Denzumi, Jun Kawahara, Koji Tsuda, Hiroki Arimura, Shin-ichi Minato, Kunihiko Sadakane (2018). DenseZDD: A Compact and Fast Index for Families of Sets. Algorithms, 11, 128.

DOI

Kota Shiba, Ryo Tamura, Takako Sugiyama, Yuko Kameyama, Keiko Koda, Eri Sakon, Kosuke Minami, Huynh Thien Ngo, Gaku Imamura, Koji Tsuda, Genki Yoshikawa (2018). Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis. ACS Sensors, 3, 8, 1592-1600.

DOI

Yutaka Saito, Misaki Oikawa, Hikaru Nakazawa, Teppei Niide, Tomoshi Kameda, Koji Tsuda, Mitsuo Umetsu (2018). Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins. ACS Synthetic Biology, 7, 2014-2022.

DOI

Kei Terayama, Tomoki Yamashita, Tamio Oguchi, Koji Tsuda (2018). Fine-grained optimization method for crystal structure prediction. npj Computational Materials, 4, 32.

DOI

Ryoko Morioka, Keisuke Nansai, Koji Tsuda (2018). Role of linkage structures in supply chain for managing greenhouse gas emissions. Journal of Economic Structures, 7, 1, 7.

DOI

Thaer M. Dieb, Zhufeng Hou, Koji Tsuda (2018). Structure prediction of boron-doped graphene by machine learning. The Journal of Chemical Physics, 148, 241716.

DOI

Ryo Tamura, Koji Hukushima (2018). Bayesian optimization for computationally extensive probability distributions. PLoS ONE, 13, e0193785.

DOI

Kei Terayama, Hiroaki Iwata, Mitsugu Araki, Yasushi Okuno, Koji Tsuda (2018). Machine Learning Accelerates MD-based Binding-Pose Prediction between Ligands and Proteins. Bioinformatics, 34, 770-778.

DOI

Thaer M. Dieb, Koji Tsuda (2018). Machine Learning-Based Experimental Design in Materials Science. In: Tanaka I. (eds) Nanoinformatics.Springer, Singapore, pp. 65-74.

DOI

Tomoki Yamashita, Nobuya Sato, Hiori Kino, Takashi Miyake, Koji Tsuda, Tamio Oguchi (2018). Crystal structure prediction accelerated by Bayesian optimization. Physical Review Materials, 2, 013803.

DOI

Yang Xiufeng, J. Zhang, Kazuki Yoshizoe, Kei Terayama, Koji Tsuda (2017). ChemTS: an efficient python library for de novo molecular generation. Science and Technology of Advanced Materials, 18, 972-976.

DOI

H. Oda, S. Kiyohara, Koji Tsuda, T. Mizoguchi (2017). Transfer Learning to Accelerate Interface Structure Searches. Journal of the Physical Society of Japan, 86, 123601.

DOI

Yang Xiufeng, Kazuki Yoshizoe, A. Taneda, Koji Tsuda (2017). RNA inverse folding using Monte Carlo tree search. BMC Bioinformatics, 18:468.

DOI

T.L. Pham, H. Kino, K. Terakura, T. Miyake, Koji Tsuda, I. Takigawa, H.C. Dam (2017). Machine learning reveals orbital interaction in materials. Science and Technology of Advanced Materials, 18, 756-765.

DOI

M. Sugiyama, H. Nakahara, Koji Tsuda (2017). Tensor Balancing on Statistical Manifold. Proceedings of the 34th International Conference on Machine Learning (ICML 2017), pp. 3270-3279.

S. Suzumura, K. Nakagawa, Y. Umezu, Koji Tsuda, I. Takeuchi (2017). Selective Inference for Sparse High-Order Interaction Models. Proceedings of the 34th International Conference on Machine Learning (ICML 2017), pp. 3338-3347.

Thaer M. Dieb, S. Ju, Kazuki Yoshizoe, Z. Hou, J. Shiomi, Koji Tsuda (2017). MDTS: automatic complex materials design using Monte Carlo tree search. Science and Technology of Advanced Materials, 18, 498-503.

DOI

S. Ju, T. Shiga, L. Feng, Z. Hou, Koji Tsuda, J. Shiomi (2017). Designing Nanostructures for Phonon Transport via Bayesian Optimization. Physical Review X, 7, 021024.

DOI

竹内一郎, 中川和也, Koji Tsuda (2017). 高次交互作用モデリングのための機械学習アルゴリズム. 日本ロボット学会誌, 3, 215-220.

DOI

M. Shiga, S. Muto, K. Tatsumi, Koji Tsuda (2016). Matrix Factorization for Automatic Chemical Mapping from Electron Microscopic Spectral Imaging Datasets. Transactions of the Materials Research Society of Japan, 41, 333-336.

DOI

Aika Terada, R. Yamada, Koji Tsuda, J. Sese (2016). LAMPLINK: detection of statistically significant SNP combinations from GWAS data. Bioinformatics, 32 (22), 3513-3515.

DOI

H. Arai, J. Sakuma, Koji Tsuda (2016). Quantifying Genomic Privacy in Genetic Test Results. 3rd International Workshop on Genome Privacy Security (Genopri 2016).

M. Shiga, K. Tatsumi, S. Muto, Koji Tsuda, Y. Yamamoto, T. Mori, T. Tanji (2016). Sparse Modeling of EELS and EDX Spectral Imaging Data by Nonnegative Matrix Factorization. Ultramicroscopy, 170, 43-59.

DOI

Thaer M. Dieb, Koji Tsuda (2016). DAMAS: An Annotation Support Tool for Materials Information. In Proceeding of the 5th Asian Materials Data Symposium (AMDS2016), pp. 242-245, Hanoi, Vietnam. Oct.30 – Nov. 2.

David duVerle, S. Yotsukura, S. Nomura, H. Aburatani, Koji Tsuda (2016). CellTree: an R/bioconductor package to infer the hierarchical structure of cell populations from single-cell RNA-seq data. BMC Bioinformatics, 17, 363.

DOI

M. Sugiyama, H. Nakahara, Koji Tsuda (2016). Information Decomposition on Structured Space. 2016 IEEE International Symposium on Information Theory, pages 575-579.

DOI

K. Nakagawa, S. Suzumura, M. Karasuyama, Koji Tsuda, I. Takeuchi (2016). Safe Pattern Pruning: An Efficient Approach for Predictive Pattern Mining. 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pages 1785-1794.

DOI

Tsuyoshi Ueno, Trevor David Rhone, Z. Hou, T. Mizoguchi, Koji Tsuda (2016). COMBO: An Efficient Bayesian Optimization Library for Materials Science. Materials Discovery, 4, 18-21.

DOI

I. Takigawa, K. Shimizu, Koji Tsuda, S. Takakusagi (2016). Machine-learning prediction of d-band center for metals and bimetals. RSC Advances, 6, 52587-52595.

DOI

Aika Terada, David duVerle, Koji Tsuda (2016). Significant Pattern Mining with Confounding Variables. 20th Pacific Asia Conference on Knowledge Discovery, Data Mining (PAKDD), pp. 277-289.

DOI

S. Kiyohara, H. Oda, Koji Tsuda, T. Mizoguchi (2016). Acceleration of stable interface structure searching using a kriging approach . Japanese Journal of Applied Physics, 55, 045502.

DOI

A. Seko, A. Togo, H. Hayashi, Koji Tsuda, L. Chaput, I. Tanaka (2015). Prediction of low-thermal-conductivity compounds with first-principles anharmonic lattice-dynamics calculations and Bayesian optimization. Physical Review Letters, 115, 205901.

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K. Shimizu, K. Nuida, H. Arai, S. Mitsunari, N. Attrapadung, M. Hamada, Koji Tsuda, T. Hirokawa, J. Sakuma, G. Hanaoka, K. Asai (2015). Privacy-preserving search for chemical compound databases. BMC Bioinformatics, 16(Suppl 18):S6.

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J. Sese, Aika Terada, Y. Saito, Koji Tsuda (2015). Statistically significant subgraphs for genome-wide association study. JMLR: Workshop and Conference Proceedings, 47:29–36.

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Y. Baba, H. Kashima, Y. Nohara, E. Kai, P. Ghosh, R. Islam, A. Ahmed, M. Kuroda, S. Inoue, T. Hiramatsu, M. Kimura, S. Shimizu, K. Kobayashi, Koji Tsuda, M. Sugiyama, M. Blondel, N. Ueda, M. Kitsuregawa, N. Nakashima (2015). Predictive Approaches for Low-cost Preventive Medicine Program in Developing Countries. Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), pp. 1681-1690.

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武藤俊介, 志賀元紀, 巽一厳, Koji Tsuda (2015). ナノ電子顕微分光における情報処理技法の応用. セラミックス, 50(7), pp.527-530.

David duVerle, S. Kawasaki, Y. Yamada, J. Sakuma, Koji Tsuda (2015). Privacy-Preserving Statistical Analysis by Exact Logistic Regression. 2nd International Workshop on Genome Privacy and Security (Genopri’15), pages 7-16.

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T. Toda, Koji Tsuda (2015). BDD Construction for All Solutions SAT and Efficient Caching Mechanism. 30th Annual ACM Symposium on Applied Computing, pp. 1880-1886.

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T. Toda, S. Takeuchi, Koji Tsuda, S. Minato (2015). Superset Generation on Decision Diagrams. 9th International Workshop on Algorithms and Computation (WALCOM 2015), pp. 317-322.

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Y. Nohara, E. Kai, P. P. Ghosh, R. Islam, A. Ahmed, M. Kuroda, S. Inoue, T. Hiramatsu, M. Kimura, S. Shimizu, K. Kobayashi, Y. Baba, H. Kashima, Koji Tsuda, M. Sugiyama, M. Blondel, N. Ueda, M. Kitsuregawa, N. Nakashima (2015). Health Checkup and Telemedical Intervention Program for Preventive Medicine in Developing Countries. Verification Study, J. Med. Internet Res., vol. 17, no. 1, p. e2.

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K. Moridomi, K. Hatano, E. Takimoto, Koji Tsuda (2014). Online matrix prediction for sparse loss matrices. 6th Asian Conference on Machine Learning, pp. 250-265.

H. Sasakawa, H. Harada, David duVerle, H. Arimura, Koji Tsuda, J. Sakuma (2014). Obivious Evaluation of Non-deterministic Finite Automata with Application to Privacy-Preserving Virus Genome Detection. Proceedings of the 13th ACM Workshop on Privacy in the Electronic Society, pages 21-30.

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Koji Tsuda (2014). ビッグデータからの科学的発見をもたらす統計手法. ファルマシア, 50(10), 993-997.

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S. Minato, T. Uno, Koji Tsuda, Aika Terada, J. Sese (2014). A Fast Method of Statistical Assessment for Combinatorial Hypotheses Based on Frequent Itemset Enumeration. ECMLPKDD, pages 422-436.

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森岡涼子, Koji Tsuda (2014). 情報幾何的分解に基づく地方産業連関表の将来推計. 京都大学数理解析研究所講究録 1916:85-102.

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S. Denzumi, J. Kawahara, Koji Tsuda, H. Arimura, S. Minato, K. Sadakane (2014). DenseZDD: A Compact and Fast Index for Families of Sets. Symposium on Experimental Algorithms, pages 187-198.

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Koji Tsuda, Aika Terada, 瀬々潤 (2014). 生命科学データからの組み合わせ発見問題. 電子情報通信学会誌, 97, 5, pp.359-363.

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瀬々潤, Aika Terada, Koji Tsuda (2014). 網羅的トランスオミクスにおけるビッグデータの解析. 実験医学 32(8): 1210 -1214.

A. Seko, T. Maekawa, Koji Tsuda, I. Tanaka (2014). Machine learning with systematic density-functional theory calculations: Application to melting temperatures of single- and binary-component solids. Physical Review B, 89:054303.

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T. Inoue, K. Takano, T. Watanabe, J. Kawahara, R. Yoshinaka, A. Kishimoto, Koji Tsuda, S. Minato, Y. Hayashi (2014). Distribution Loss Minimization with Guaranteed Error Bound. IEEE Transactions on Smart Grid, 5(1):102-111.

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