| Approximation ratios of graph neural networks for combinatorial problems R Sato, M Yamada, H Kashima arXiv preprint arXiv:1905.10261, 2019 | 33 | 2019 |
| A survey on the expressive power of graph neural networks R Sato arXiv preprint arXiv:2003.04078, 2020 | 30 | 2020 |
| Random features strengthen graph neural networks R Sato, M Yamada, H Kashima Proceedings of the 2021 SIAM International Conference on Data Mining (SDM …, 2021 | 17 | 2021 |
| Short-term precipitation prediction with skip-connected prednet R Sato, H Kashima, T Yamamoto International Conference on Artificial Neural Networks, 373-382, 2018 | 10 | 2018 |
| Fast Unbalanced Optimal Transport on a Tree R Sato, M Yamada, H Kashima arXiv preprint arXiv:2006.02703, 2020 | 7 | 2020 |
| Fast and robust comparison of probability measures in heterogeneous spaces R Sato, M Cuturi, M Yamada, H Kashima arXiv preprint arXiv:2002.01615, 2020 | 3 | 2020 |
| Constant time graph neural networks R Sato, M Yamada, H Kashima arXiv preprint arXiv:1901.07868, 2019 | 3 | 2019 |
| Learning to Sample Hard Instances for Graph Algorithms R Sato, M Yamada, H Kashima Asian Conference on Machine Learning, 503--518, 2019 | 3* | 2019 |
| Poincare: Recommending publication venues via treatment effect estimation R Sato, M Yamada, H Kashima arXiv preprint arXiv:2010.09157, 2020 | 1 | 2020 |
| Feature robust optimal transport for high-dimensional data M Petrovich, C Liang, R Sato, Y Liu, YHH Tsai, L Zhu, Y Yang, ... arXiv preprint arXiv:2005.12123, 2020 | 1 | 2020 |
| Re-evaluating Word Mover's Distance R Sato, M Yamada, H Kashima arXiv preprint arXiv:2105.14403, 2021 | | 2021 |
| Enumerating Fair Packages for Group Recommendations R Sato arXiv preprint arXiv:2105.14423, 2021 | | 2021 |
| Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? R Sato arXiv preprint arXiv:2105.12353, 2021 | | 2021 |
| Supervised Tree-Wasserstein Distance Y Takezawa, R Sato, M Yamada arXiv preprint arXiv:2101.11520, 2021 | | 2021 |
Makoto YamadaKyoto University / RIKEN Center for Advanced Intelligence Project (AIP)Verified email at i.kyoto-u.ac.jp
