ChemTS: an efficient python library for de novo molecular generation X Yang, J Zhang, K Yoshizoe, K Terayama, K Tsuda Science and technology of advanced materials 18 (1), 972-976, 2017 | 273 | 2017 |
Faster autoaugment: Learning augmentation strategies using backpropagation R Hataya, J Zdenek, K Yoshizoe, H Nakayama Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 228 | 2020 |
MDTS: automatic complex materials design using Monte Carlo tree search T M. Dieb, S Ju, K Yoshizoe, Z Hou, J Shiomi, K Tsuda Science and technology of advanced materials 18 (1), 498-503, 2017 | 70 | 2017 |
Scalable distributed monte-carlo tree search K Yoshizoe, A Kishimoto, T Kaneko, H Yoshimoto, Y Ishikawa Proceedings of the International Symposium on Combinatorial Search 2 (1 …, 2011 | 56 | 2011 |
On the possibility of short-term traffic prediction during disaster with machine learning approaches: An exploratory analysis M Chikaraishi, P Garg, V Varghese, K Yoshizoe, J Urata, Y Shiomi, ... Transport Policy 98, 91-104, 2020 | 54 | 2020 |
Meta approach to data augmentation optimization R Hataya, J Zdenek, K Yoshizoe, H Nakayama Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 50 | 2022 |
Lambda Depth-First Proof Number Search and Its Application to Go. K Yoshizoe, A Kishimoto, M Müller IJCAI, 2404-2409, 2007 | 47 | 2007 |
NMR-TS: de novo molecule identification from NMR spectra J Zhang, K Terayama, M Sumita, K Yoshizoe, K Ito, J Kikuchi, K Tsuda Science and technology of advanced materials 21 (1), 552-561, 2020 | 39 | 2020 |
CompRet: a comprehensive recommendation framework for chemical synthesis planning with algorithmic enumeration R Shibukawa, S Ishida, K Yoshizoe, K Wasa, K Takasu, Y Okuno, ... Journal of cheminformatics 12, 1-14, 2020 | 33 | 2020 |
Monte Carlo Go has a way to go H Yoshimoto, K Yoshizoe, T Kaneko, A Kishimoto, K Taura AAAI 6, 1070-1075, 2006 | 33 | 2006 |
De novo creation of a naked eye–detectable fluorescent molecule based on quantum chemical computation and machine learning M Sumita, K Terayama, N Suzuki, S Ishihara, R Tamura, MK Chahal, ... Science Advances 8 (10), eabj3906, 2022 | 29 | 2022 |
RNA inverse folding using Monte Carlo tree search X Yang, K Yoshizoe, A Taneda, K Tsuda BMC bioinformatics 18, 1-12, 2017 | 27 | 2017 |
Accelerated UCT and its application to two-player games J Hashimoto, A Kishimoto, K Yoshizoe, K Ikeda Advances in Computer Games: 13th International Conference, ACG 2011, Tilburg …, 2012 | 25 | 2012 |
A study on security evaluation methodology for image-based biometrics authentication systems Y Tanabe, K Yoshizoe, H Imai 2009 IEEE 3rd international conference on biometrics: Theory, applications …, 2009 | 24 | 2009 |
Practical massively parallel monte-carlo tree search applied to molecular design X Yang, TK Aasawat, K Yoshizoe arXiv preprint arXiv:2006.10504, 2020 | 23 | 2020 |
MP-LAMP: parallel detection of statistically significant multi-loci markers on cloud platforms K Yoshizoe, A Terada, K Tsuda Bioinformatics 34 (17), 3047-3049, 2018 | 10 | 2018 |
Graph energy-based model for substructure preserving molecular design R Hataya, H Nakayama, K Yoshizoe arXiv preprint arXiv:2102.04600, 2021 | 9 | 2021 |
Speculative parallel execution on JVM K Yoshizoe 1st UK Workshop on Java for High Performance Network Computing, 1998 | 9 | 1998 |
Machine learning to reveal hidden risk combinations for the trajectory of posttraumatic stress disorder symptoms Y Takahashi, K Yoshizoe, M Ueki, G Tamiya, Y Zhiqian, Y Utsumi, ... Scientific reports 10 (1), 21726, 2020 | 8 | 2020 |
Hygn: Hybrid graph engine for numa T Aasawat, T Reza, K Yoshizoe, M Ripeanu 2020 IEEE International Conference on Big Data (Big Data), 383-390, 2020 | 7 | 2020 |