Publications

(2020). Machine Learning Meets Quantum Physics. Springer Nature.

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(2020). Pushing property limits in materials discovery via boundless objective-free exploration. Chemical Science, 11, 5959-5968.

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(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

(2020). Artificial Neural Networks Applied as Molecular Wave Function Solvers. Journal of Chemical Theory and Computation, 16, 3513-3529.

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(2020). Computer Vision-Based Approach for Quantifying Occupational Therapists Qualitative Evaluations of Postural Control. Occupational Therapy International, 8542191.

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(2020). Data Integration for Accelerated Materials Design via Preference Learning. New Journal of Physics, 22, 055001.

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(2020). Designing metamaterials with quantum annealing and factorization machines. Phys. Rev. Research 2, 013319.

DOI arXiv

(2019). Deep-learning-based quality filtering of mechanically exfoliated 2D crystals. npj Computational Materials, 5, 124.

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(2019). Efficient query autocompletion with edit distance-based error tolerance. The VLDB Journal.

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(2019). Legendre decomposition for tensors. Journal of Statistical Mechanics, 124017.

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(2019). evERdock BAI: Machine-learning-guided selection of protein-protein complex structure. Journal of Chemical Physics, 151, 215104.

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(2019). Monte Carlo tree search for materials design and discovery. MRS Communications, 9, 532-536.

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(2019). Machine-Learning-Assisted Development and Theoretical Consideration for the Al2Fe3Si3 Thermoelectric Material. ACS Applied Materials and Interfaces, 11, 11545-11554.

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(2019). Application of Bayesian Optimization for Pharmaceutical Product Development. Journal of Pharmaceutical Innovation, 1-11.

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(2019). Efficient construction method for phase diagrams using uncertainty sampling. Physical Review Materials, i3, 3, 033802.

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(2019). An interpretable machine learning model for diagnosis of Alzheimer's disease. PeerJ Life & Environment, 7, e6543.

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(2019). Ultranarrow-Band Wavelength-Selective Thermal Emission with Aperiodic Multilayered Metamaterials Designed by Bayesian Optimization. ACS Central Science, 5, 2, 319-326.

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(2019). Data-driven analysis of electron relaxation times in PbTe-type thermoelectric materials. Science and Technology of Advanced Materials, 20, 511-520.

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(2018). Legendre Decomposition for Tensors. Advances in Neural Information Processing Systems, 31, 8811-8821.

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(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.

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(2018). Data-driven approach for the prediction and interpretation of core-electron loss spectroscopy. Scientific Reports, 8, 13548.

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(2018). DenseZDD: A Compact and Fast Index for Families of Sets. Algorithms, 11, 128.

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(2018). Functional Nanoparticles-Coated Nanomechanical Sensor Arrays for Machine Learning-Based Quantitative Odor Analysis. ACS Sensors, 3, 8, 1592-1600.

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(2018). Machine-Learning-Guided Mutagenesis for Directed Evolution of Fluorescent Proteins. ACS Synthetic Biology, 7, 2014-2022.

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(2018). Fine-grained optimization method for crystal structure prediction. npj Computational Materials, 4, 32.

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(2018). Role of linkage structures in supply chain for managing greenhouse gas emissions. Journal of Economic Structures, 7, 1, 7.

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(2018). Structure prediction of boron-doped graphene by machine learning. The Journal of Chemical Physics, 148, 241716.

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(2018). Machine Learning Accelerates MD-based Binding-Pose Prediction between Ligands and Proteins. Bioinformatics, 34, 770-778.

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

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(2018). Crystal structure prediction accelerated by Bayesian optimization. Physical Review Materials, 2, 013803.

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(2017). ChemTS: an efficient python library for de novo molecular generation. Science and Technology of Advanced Materials, 18, 972-976.

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(2017). Transfer Learning to Accelerate Interface Structure Searches. Journal of the Physical Society of Japan, 86, 123601.

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(2017). Machine learning reveals orbital interaction in materials. Science and Technology of Advanced Materials, 18, 756-765.

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

(2017). Selective Inference for Sparse High-Order Interaction Models. Proceedings of the 34th International Conference on Machine Learning (ICML 2017), pp. 3338-3347.

(2017). MDTS: automatic complex materials design using Monte Carlo tree search. Science and Technology of Advanced Materials, 18, 498-503.

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(2017). Designing Nanostructures for Phonon Transport via Bayesian Optimization. Physical Review X, 7, 021024.

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(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.

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(2016). Matrix Factorization for Automatic Chemical Mapping from Electron Microscopic Spectral Imaging Datasets. Transactions of the Materials Research Society of Japan, 41, 333-336.

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(2016). Quantifying Genomic Privacy in Genetic Test Results. 3rd International Workshop on Genome Privacy Security (Genopri 2016).

(2016). Sparse Modeling of EELS and EDX Spectral Imaging Data by Nonnegative Matrix Factorization. Ultramicroscopy, 170, 43-59.

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(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.

(2016). Information Decomposition on Structured Space. 2016 IEEE International Symposium on Information Theory, pages 575-579.

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(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.

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(2016). Machine-learning prediction of d-band center for metals and bimetals. RSC Advances, 6, 52587-52595.

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

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(2016). Acceleration of stable interface structure searching using a kriging approach . Japanese Journal of Applied Physics, 55, 045502.

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(2015). Privacy-preserving search for chemical compound databases. BMC Bioinformatics, 16(Suppl 18):S6.

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(2015). Statistically significant subgraphs for genome-wide association study. JMLR: Workshop and Conference Proceedings, 47:29–36.

Source Document

(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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(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.

(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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(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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(2015). Superset Generation on Decision Diagrams. 9th International Workshop on Algorithms and Computation (WALCOM 2015), pp. 317-322.

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(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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(2014). Online matrix prediction for sparse loss matrices. 6th Asian Conference on Machine Learning, pp. 250-265.

(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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(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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(2014). DenseZDD: A Compact and Fast Index for Families of Sets. Symposium on Experimental Algorithms, pages 187-198.

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(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.

Source Document

(2014). Distribution Loss Minimization with Guaranteed Error Bound. IEEE Transactions on Smart Grid, 5(1):102-111.

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