| Approximation ratios of graph neural networks for combinatorial problems R Sato, M Yamada, H Kashima arXiv preprint arXiv:1905.10261, 2019 | 16 | 2019 |
| A survey on the expressive power of graph neural networks R Sato arXiv preprint arXiv:2003.04078, 2020 | 14 | 2020 |
| Random features strengthen graph neural networks R Sato, M Yamada, H Kashima arXiv preprint arXiv:2002.03155, 2020 | 11 | 2020 |
| Short-term precipitation prediction with skip-connected prednet R Sato, H Kashima, T Yamamoto International Conference on Artificial Neural Networks, 373-382, 2018 | 8 | 2018 |
| Constant time graph neural networks R Sato, M Yamada, H Kashima arXiv preprint arXiv:1901.07868, 2019 | 3 | 2019 |
| Fast unbalanced optimal transport on tree R Sato, M Yamada, H Kashima arXiv preprint arXiv:2006.02703, 2020 | 1 | 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 | 1 | 2020 |
| Learning to Sample Hard Instances for Graph Algorithms R Sato, M Yamada, H Kashima Asian Conference on Machine Learning, 503--518, 2019 | 1 | 2019 |
| Poincare: Recommending Publication Venues via Treatment Effect Estimation R Sato, M Yamada, H Kashima arXiv preprint arXiv:2010.09157, 2020 | | 2020 |
