Random features strengthen graph neural networks R Sato, M Yamada, H Kashima Proceedings of the 2021 SIAM international conference on data mining (SDM …, 2021 | 218 | 2021 |

A survey on the expressive power of graph neural networks R Sato arXiv preprint arXiv:2003.04078, 2020 | 199 | 2020 |

Approximation ratios of graph neural networks for combinatorial problems R Sato, M Yamada, H Kashima Advances in Neural Information Processing Systems 32, 2019 | 126 | 2019 |

Fast unbalanced optimal transport on a tree R Sato, M Yamada, H Kashima Advances in neural information processing systems 33, 19039-19051, 2020 | 28 | 2020 |

Short-term precipitation prediction with skip-connected prednet R Sato, H Kashima, T Yamamoto Artificial Neural Networks and Machine Learning–ICANN 2018: 27th …, 2018 | 27 | 2018 |

Re-evaluating word mover’s distance R Sato, M Yamada, H Kashima International Conference on Machine Learning, 19231-19249, 2022 | 25 | 2022 |

Enumerating fair packages for group recommendations R Sato Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 18 | 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 | 18 | 2020 |

Fixed support tree-sliced Wasserstein barycenter Y Takezawa, R Sato, Z Kozareva, S Ravi, M Yamada arXiv preprint arXiv:2109.03431, 2021 | 15 | 2021 |

Supervised tree-wasserstein distance Y Takezawa, R Sato, M Yamada International Conference on Machine Learning, 10086-10095, 2021 | 11 | 2021 |

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 | 10 | 2022 |

Embarrassingly simple text watermarks R Sato, Y Takezawa, H Bao, K Niwa, M Yamada arXiv preprint arXiv:2310.08920, 2023 | 8 | 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 | 8 | 2023 |

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 |

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 | 8 | 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 | 7 | 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 | 7 | 2022 |

Retrieving black-box optimal images from external databases R Sato Proceedings of the Fifteenth ACM International Conference on Web Search and …, 2022 | 7 | 2022 |

Clear: A fully user-side image search system R Sato Proceedings of the 31st ACM International Conference on Information …, 2022 | 6 | 2022 |

Graph neural networks can recover the hidden features solely from the graph structure R Sato International Conference on Machine Learning, 30062-30079, 2023 | 5 | 2023 |