| Chainer: a next-generation open source framework for deep learning S Tokui, K Oono, S Hido, J Clayton Proceedings of workshop on machine learning systems (LearningSys) in the …, 2015 | 1102 | 2015 |
| Learning discrete representations via information maximizing self-augmented training W Hu, T Miyato, S Tokui, E Matsumoto, M Sugiyama International conference on machine learning, 1558-1567, 2017 | 500 | 2017 |
| Adversarial attacks and defences competition A Kurakin, I Goodfellow, S Bengio, Y Dong, F Liao, M Liang, T Pang, ... The NIPS'17 Competition: Building Intelligent Systems, 195-231, 2018 | 327 | 2018 |
| Chainer: A deep learning framework for accelerating the research cycle S Tokui, R Okuta, T Akiba, Y Niitani, T Ogawa, S Saito, S Suzuki, ... Proceedings of the 25th ACM SIGKDD International Conference on Knowledge …, 2019 | 155 | 2019 |
| Machine learning heterogeneous edge device, method, and system D Okanohara, JB Clayton, T Nishikawa, S Hido, N Kubota, N Ota, S Tokui US Patent 9,990,587, 2018 | 84 | 2018 |
| Machine learning with model filtering and model mixing for edge devices in a heterogeneous environment D Okanohara, JB Clayton, T Nishikawa, S Hido, N Kubota, N Ota, S Tokui US Patent 10,387,794, 2019 | 61 | 2019 |
| Jubatus: An open source platform for distributed online machine learning S Hido, S Tokui, S Oda NIPS 2013 Workshop on Big Learning, Lake Tahoe, 2013 | 42 | 2013 |
| Evaluating the variance of likelihood-ratio gradient estimators S Tokui, I Sato International Conference on Machine Learning, 3414-3423, 2017 | 20 | 2017 |
| Disentanglement Analysis with Partial Information Decomposition S Tokui, I Sato arXiv preprint arXiv:2108.13753, 2021 | 13 | 2021 |
| Information processing device and information processing method S Tokui, Y Unno, O Kenta, R Okuta US Patent 11,521,070, 2022 | 10 | 2022 |
| Machine learning heterogeneous edge device, method, and system D Okanohara, J Clayton, T Nishikawa, S Hido, N Kubota, N Ota, S Tokui US Patent App. 15/970,294, 2018 | 9 | 2018 |
| Reparameterization trick for discrete variables S Tokui arXiv preprint arXiv:1611.01239, 2016 | 8 | 2016 |
| Unsupervised Discrete Representation Learning W Hu, T Miyato, S Tokui, E Matsumoto, M Sugiyama Explainable AI: Interpreting, Explaining and Visualizing Deep Learning, 97-119, 2019 | 3 | 2019 |
| Information processing device and information processing method S Tokui, Y Unno, O Kenta, R Okuta US Patent App. 16/551,435, 2019 | 2 | 2019 |
| Machine learning heterogeneous edge device, method, and system JB CLAYTON, D OKANOHARA, T Nishikawa, S Hido, N KUBOTA, N Ota, ... | 1 | 2016 |
| Locally optimized hashing for nearest neighbor search S Tokui, I Sato, H Nakagawa Advances in Knowledge Discovery and Data Mining: 19th Pacific-Asia …, 2015 | 1 | 2015 |
| Information processing device and information processing method S Tokui, Y Unno, O Kenta, R Okuta US Patent 11,915,146, 2024 | | 2024 |
| Information processing device and information processing method S Tokui, Y Unno, O Kenta, R Okuta US Patent App. 18/487,217, 2024 | | 2024 |
| Compiler, generation method, chip, and execution method S Tokui US Patent App. 18/048,934, 2023 | | 2023 |
| Training apparatus, training method, non-transitory computer readable medium, and model generating method S Tokui, D Nishino, HV Yamazaki, SEO Naotoshi, A Imanishi US Patent App. 16/693,754, 2020 | | 2020 |
