| Hyperbolic neural networks++ R Shimizu, Y Mukuta, T Harada arXiv preprint arXiv:2006.08210, 2020 | 120 | 2020 |
| Common subspace for model and similarity: Phrase learning for caption generation from images Y Ushiku, M Yamaguchi, Y Mukuta, T Harada Proceedings of the IEEE international conference on computer vision, 2668-2676, 2015 | 63 | 2015 |
| Multi-stage pathological image classification using semantic segmentation S Takahama, Y Kurose, Y Mukuta, H Abe, M Fukayama, A Yoshizawa, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 49 | 2019 |
| Fully spiking variational autoencoder H Kamata, Y Mukuta, T Harada Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 7059-7067, 2022 | 28 | 2022 |
| Neural star domain as primitive representation Y Kawana, Y Mukuta, T Harada Advances in Neural Information Processing Systems 33, 7875-7886, 2020 | 24 | 2020 |
| Finding and generating a missing part for story completion Y Mori, H Yamane, Y Mukuta, T Harada Proceedings of the The 4th Joint SIGHUM Workshop on Computational …, 2020 | 21 | 2020 |
| Modeling the variability of active galactic nuclei by an infinite mixture of Ornstein–Uhlenbeck (OU) processes T Takata, Y Mukuta, Y Mizumoto The Astrophysical Journal 869 (2), 178, 2018 | 19 | 2018 |
| Spherical image generation from a single image by considering scene symmetry T Hara, Y Mukuta, T Harada Proceedings of the AAAI Conference on Artificial Intelligence 35 (2), 1513-1521, 2021 | 16 | 2021 |
| Backprop induced feature weighting for adversarial domain adaptation with iterative label distribution alignment T Westfechtel, HW Yeh, Q Meng, Y Mukuta, T Harada Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2023 | 15 | 2023 |
| Scalable generative models for graphs with graph attention mechanism W Kawai, Y Mukuta, T Harada arXiv preprint arXiv:1906.01861, 2019 | 15 | 2019 |
| Texture-based classification of significant stenosis in CCTA multi-view images of coronary arteries A Tejero-de-Pablos, K Huang, H Yamane, Y Kurose, Y Mukuta, J Iho, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019 | 14 | 2019 |
| Kernel approximation via empirical orthogonal decomposition for unsupervised feature learning Y Mukuta, T Harada Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 14 | 2016 |
| Deep modality invariant adversarial network for shared representation learning K Saito, Y Mukuta, Y Ushiku, T Harada Proceedings of the IEEE International Conference on Computer Vision …, 2017 | 12* | 2017 |
| Probabilistic partial canonical correlation analysis Y Mukuta International Conference on Machine Learning, 1449-1457, 2014 | 12 | 2014 |
| Rethinking task and metrics of instance segmentation on 3D point clouds K Arase, Y Mukuta, T Harada Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2019 | 10 | 2019 |
| Unsupervised pose-aware part decomposition for man-made articulated objects Y Kawana, Y Mukuta, T Harada European Conference on Computer Vision, 558-575, 2022 | 8 | 2022 |
| Toward a better story end: Collecting human evaluation with reasons Y Mori, H Yamane, Y Mukuta, T Harada Proceedings of the 12th International Conference on Natural Language …, 2019 | 8 | 2019 |
| MIL at ImageCLEF 2014: Scalable System for Image Annotation. A Kanehira, M Hidaka, Y Mukuta, Y Tsuchiya, T Mano, T Harada CLEF (Working Notes), 372-379, 2014 | 7 | 2014 |
| Unsupervised pose-aware part decomposition for 3d articulated objects Y Kawana, Y Mukuta, T Harada arXiv preprint arXiv:2110.04411, 2021 | 6 | 2021 |
| Gram: Scalable generative models for graphs with graph attention mechanism W Kawai, Y Mukuta, T Harada arXiv preprint arXiv:1906.01861, 2019 | 6 | 2019 |
