| Temporal generative adversarial nets with singular value clipping M Saito, E Matsumoto, S Saito Proceedings of the IEEE international conference on computer vision, 2830-2839, 2017 | 737 | 2017 |
| 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 | 582 | 2017 |
| Decomposing nerf for editing via feature field distillation S Kobayashi, E Matsumoto, V Sitzmann Advances in neural information processing systems 35, 23311-23330, 2022 | 349 | 2022 |
| Machine learning device, robot system, and machine learning method for learning workpiece picking operation T Yamazaki, T Oyama, S Suyama, K Nakayama, H Kumiya, H Nakagawa, ... US Patent 10,717,196, 2020 | 80 | 2020 |
| Surface-aligned neural radiance fields for controllable 3d human synthesis T Xu, Y Fujita, E Matsumoto Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 62 | 2022 |
| Machine learning method and machine learning device for learning fault conditions, and fault prediction device and fault prediction system including the machine learning device S Inagaki, H Nakagawa, D Okanohara, R Okuta, E Matsumoto, K Kawaai US Patent 10,317,853, 2019 | 59 | 2019 |
| Machine learning Method and machine learning device for learning fault conditions, and fault prediction device and fault prediction system including the machine learning device S Inagaki, H Nakagawa, D Okanohara, R Okuta, E Matsumoto, K Kawaai US Patent 11,275,345, 2022 | 31 | 2022 |
| Machine learning device, robot controller, robot system, and machine learning method for learning action pattern of human T Tsuda, D Okanohara, R Okuta, E Matsumoto, K Kawaai US Patent App. 15/222,947, 2017 | 29 | 2017 |
| End-to-end learning of object grasp poses in the Amazon Robotics Challenge E Matsumoto, M Saito, A Kume, J Tan Advances on Robotic Item Picking: Applications in Warehousing & E-Commerce …, 2020 | 28 | 2020 |
| Robot system and workpiece picking method T Yamazaki, D Okanohara, E Matsumoto US Patent 11,845,194, 2023 | 20 | 2023 |
| Map-based multi-policy reinforcement learning: enhancing adaptability of robots by deep reinforcement learning A Kume, E Matsumoto, K Takahashi, W Ko, J Tan arXiv preprint arXiv:1710.06117, 2017 | 20 | 2017 |
| Machine learning device, robot controller, robot system, and machine learning method for learning action pattern of human T Tsuda, D Okanohara, R Okuta, E Matsumoto, K Kawaai US Patent 10,807,235, 2020 | 16 | 2020 |
| Learning device unit D Okanohara, R Okuta, E Matsumoto, K Kawaai US Patent 11,475,289, 2022 | 10 | 2022 |
| Learning device, learning method, learning model, detection device and grasping system H Kusano, K Ayaka, E Matsumoto US Patent 11,034,018, 2021 | 9 | 2021 |
| Addressing class imbalance in scene graph parsing by learning to contrast and score H Huang, S Saito, Y Kikuchi, E Matsumoto, W Tang, PS Yu Proceedings of the Asian Conference on Computer Vision, 2020 | 6 | 2020 |
| Machine learning device, robot controller, robot system, and machine learning method for learning action pattern of human T Tsuda, D Okanohara, R Okuta, E Matsumoto, K Kawaai US Patent 11,904,469, 2024 | 5 | 2024 |
| Machine learning device, robot system, and machine learning method for learning object picking operation T Yamazaki, T Oyama, S Suyama, K Nakayama, H Kumiya, H Nakagawa, ... US Patent 11,780,095, 2023 | 4 | 2023 |
| Multi-view neural surface reconstruction with structured light C Li, T Hashimoto, E Matsumoto, H Kato arXiv preprint arXiv:2211.11971, 2022 | 4 | 2022 |
| Automatic coloring of line drawing E Matsumoto US Patent 11,386,587, 2022 | 4 | 2022 |
| 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 | 4 | 2019 |
