| Three levels of data-driven science Y Igarashi, K Nagata, T Kuwatani, T Omori, Y Nakanishi-Ohno, M Okada Journal of Physics: Conference Series 699 (1), 012001, 2016 | 66 | 2016 |
| Exhaustive search for sparse variable selection in linear regression Y Igarashi, H Takenaka, Y Nakanishi-Ohno, M Uemura, S Ikeda, M Okada Journal of the Physical Society of Japan 87 (4), 044802, 2018 | 47 | 2018 |
| Liquid electrolyte informatics using an exhaustive search with linear regression K Sodeyama, Y Igarashi, T Nakayama, Y Tateyama, M Okada Physical Chemistry Chemical Physics 20 (35), 22585-22591, 2018 | 41 | 2018 |
| Machine learning prediction of coordination energies for alkali group elements in battery electrolyte solvents A Ishikawa, K Sodeyama, Y Igarashi, T Nakayama, Y Tateyama, M Okada Physical Chemistry Chemical Physics 21 (48), 26399-26405, 2019 | 37 | 2019 |
| Materials informatics for 2D materials combined with sparse modeling and chemical perspective: Toward small-data-driven chemistry and materials science Y Oaki, Y Igarashi Bulletin of the Chemical Society of Japan 94 (10), 2410-2422, 2021 | 35 | 2021 |
| Materials‐Informatics‐Assisted High‐Yield Synthesis of 2D Nanomaterials through Exfoliation YO Gentoku Nakada, Yasuhiko Igarashi, Hiroaki Imai ADVANCED Theory and Simulations 2 (4), 1800180, 2019 | 32 | 2019 |
| Materials Informatics: Experiment‐Oriented Materials Informatics for Efficient Exploration of Design Strategy and New Compounds for High‐Performance Organic Anode (Adv. Theory … H Numazawa, Y Igarashi, K Sato, H Imai, Y Oaki Advanced Theory and Simulations 2 (10), 1970035, 2019 | 24* | 2019 |
| ES-DoS: Exhaustive search and density-of-states estimation as a general framework for sparse variable selection Y Igarashi, H Ichikawa, Y Nakanishi-Ohno, H Takenaka, D Kawabata, ... Journal of Physics: Conference Series 1036, 012001, 2018 | 22 | 2018 |
| Lateral-size control of exfoliated transition-metal–oxide 2D materials by machine learning on small data R Mizuguchi, Y Igarashi, H Imai, Y Oaki Nanoscale 13 (6), 3853-3859, 2021 | 21 | 2021 |
| Prediction of high-beta disruptions in JT-60U based on sparse modeling using exhaustive search T Yokoyama, Y Miyoshi, R Hiwatari, A Isayama, G Matsunaga, N Oyama, ... Fusion Engineering and Design 140, 67-80, 2019 | 20 | 2019 |
| Sparse modeling of an extended X-ray absorption fine-structure spectrum based on a single-scattering formalism I Akai, K Iwamitsu, Y Igarashi, M Okada, H Setoyama, T Okajima, Y Hirai Journal of the Physical Society of Japan 87 (7), 074003, 2018 | 18 | 2018 |
| Maximum tsunami height prediction using pressure gauge data by a Gaussian process at Owase in the Kii Peninsula, Japan Y Igarashi, T Hori, S Murata, K Sato, T Baba, M Okada Marine Geophysical Research 37, 361-370, 2016 | 16 | 2016 |
| Efficient Syntheses of 2D Materials from Soft Layered Composites Guided by Yield Prediction Model: Potential of Experiment‐Oriented Materials Informatics K Noda, Y Igarashi, H Imai, Y Oaki Advanced Theory and Simulations 3 (7), 2000084, 2020 | 15 | 2020 |
| Yield-prediction models for efficient exfoliation of soft layered materials into nanosheets K Noda, Y Igarashi, H Imai, Y Oaki Chemical Communications 57 (48), 5921-5924, 2021 | 14 | 2021 |
| A longitudinal study of infant view-invariant face processing during the first 3–8 months of life H Ichikawa, E Nakato, Y Igarashi, M Okada, S Kanazawa, MK Yamaguchi, ... Neuroimage 186, 817-824, 2019 | 14 | 2019 |
| Material search for Li-ion battery electrolytes through an exhaustive search with a Gaussian process T Nakayama, Y Igarashi, K Sodeyama, M Okada Chemical Physics Letters 731, 136622, 2019 | 13 | 2019 |
| Prompt engineering of GPT-4 for chemical research: what can/cannot be done? K Hatakeyama-Sato, N Yamane, Y Igarashi, Y Nabae, T Hayakawa Science and Technology of Advanced Materials: Methods 3 (1), 2260300, 2023 | 12 | 2023 |
| Sparse modeling for small data: case studies in controlled synthesis of 2D materials Y Haraguchi, Y Igarashi, H Imai, Y Oaki Digital Discovery 1 (1), 26-34, 2022 | 12 | 2022 |
| Statistical mechanical analysis of catastrophic forgetting in continual learning with teacher and student networks H Asanuma, S Takagi, Y Nagano, Y Yoshida, Y Igarashi, M Okada Journal of the Physical Society of Japan 90 (10), 104001, 2021 | 12 | 2021 |
| Mean field analysis of stochastic neural network models with synaptic depression Y Igarashi, M Oizumi, M Okada Journal of the Physical Society of Japan 79 (8), 084001, 2010 | 11 | 2010 |
MASATO OKADA東京大学確認したメール アドレス: edu.k.u-tokyo.ac.jp
