| Random features strengthen graph neural networks R Sato, M Yamada, H Kashima Proceedings of the 2021 SIAM international conference on data mining (SDM …, 2021 | 239 | 2021 |
| A survey on the expressive power of graph neural networks R Sato arXiv preprint arXiv:2003.04078, 2020 | 217 | 2020 |
| Approximation ratios of graph neural networks for combinatorial problems R Sato, M Yamada, H Kashima Advances in Neural Information Processing Systems 32, 2019 | 128 | 2019 |
| Short-term precipitation prediction with skip-connected prednet R Sato, H Kashima, T Yamamoto Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 31 | 2018 |
| Fast unbalanced optimal transport on a tree R Sato, M Yamada, H Kashima Advances in neural information processing systems 33, 19039-19051, 2020 | 30 | 2020 |
| Re-evaluating word mover’s distance R Sato, M Yamada, H Kashima International Conference on Machine Learning, 19231-19249, 2022 | 29 | 2022 |
| Enumerating fair packages for group recommendations R Sato Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 24 | 2022 |
| Fast and robust comparison of probability measures in heterogeneous spaces R Sato, M Cuturi, M Yamada, H Kashima arXiv preprint arXiv:2002.01615, 2020 | 19 | 2020 |
| Fixed support tree-sliced Wasserstein barycenter Y Takezawa, R Sato, Z Kozareva, S Ravi, M Yamada arXiv preprint arXiv:2109.03431, 2021 | 17 | 2021 |
| Supervised tree-wasserstein distance Y Takezawa, R Sato, M Yamada International Conference on Machine Learning, 10086-10095, 2021 | 14 | 2021 |
| Embarrassingly simple text watermarks R Sato, Y Takezawa, H Bao, K Niwa, M Yamada arXiv preprint arXiv:2310.08920, 2023 | 13 | 2023 |
| Necessary and sufficient watermark for large language models Y Takezawa, R Sato, H Bao, K Niwa, M Yamada arXiv preprint arXiv:2310.00833, 2023 | 13 | 2023 |
| Momentum tracking: Momentum acceleration for decentralized deep learning on heterogeneous data Y Takezawa, H Bao, K Niwa, R Sato, M Yamada arXiv preprint arXiv:2209.15505, 2022 | 11 | 2022 |
| Approximating 1-wasserstein distance with trees M Yamada, Y Takezawa, R Sato, H Bao, Z Kozareva, S Ravi arXiv preprint arXiv:2206.12116, 2022 | 10 | 2022 |
| Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? R Sato Proceedings of the 2022 SIAM International Conference on Data Mining (SDM …, 2022 | 9 | 2022 |
| Feature-robust optimal transport for high-dimensional data M Petrovich, C Liang, R Sato, Y Liu, YHH Tsai, L Zhu, Y Yang, ... Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 8 | 2022 |
| Constant time graph neural networks R Sato, M Yamada, H Kashima ACM Transactions on Knowledge Discovery from Data (TKDD) 16 (5), 1-31, 2022 | 8 | 2022 |
| Retrieving black-box optimal images from external databases R Sato Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 8 | 2022 |
| Clear: A fully user-side image search system R Sato Proceedings of the 31st ACM International Conference on Information …, 2022 | 7 | 2022 |
| Graph neural networks can recover the hidden features solely from the graph structure R Sato International Conference on Machine Learning, 30062-30079, 2023 | 6 | 2023 |
Makoto YamadaOIST & FlatMinima Inc.Verified email at oist.jp
