Summarizing data structures with Gaussian process and robust neighborhood preservation K Watanabe, K Maeda, T Ogawa, M Haseyama Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 2 | 2022 |
SpectralMAP: Approximating Data Manifold With Spectral Decomposition K Watanabe, K Maeda, T Ogawa, M Haseyama IEEE Access 11, 31530-31540, 2023 | 1 | 2023 |
Attention-based Multiple Instance Learning に基づく背景の多様性に頑健な道路附属物の異状判定 渡部航史, 小川直輝, 前田圭介, 小川貴弘, 長谷山美紀 AI・データサイエンス論文集 4 (3), 482-489, 2023 | 1 | 2023 |
Movie rating estimation based on weakly supervised multi-modal latent variable model K Watanabe, K Maeda, T Ogawa, M Haseyama 2021 IEEE 10th Global Conference on Consumer Electronics (GCCE), 195-196, 2021 | 1 | 2021 |
StarMAP: Global Neighbor Embedding for Faithful Data Visualization K Watanabe, K Maeda, T Ogawa, M Haseyama arXiv preprint arXiv:2502.03776, 2025 | | 2025 |
Hyperboloid GPLVM for Discovering Continuous Hierarchies via Nonparametric Estimation K Watanabe, K Maeda, T Ogawa, M Haseyama arXiv preprint arXiv:2410.16698, 2024 | | 2024 |
A Gaussian Process Decoder with Spectral Mixtures and a Locally Estimated Manifold for Data Visualization K Watanabe, K Maeda, T Ogawa, M Haseyama Applied Sciences 13 (14), 8018, 2023 | | 2023 |
Learning Graph Laplacian from Intrinsic Patterns via Gaussian Process K Watanabe, K Maeda, T Ogawa, M Haseyama ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | | 2023 |
A Note on Improvement of Supervised Latent Variable Model with Graph-Encoded Class Information K Watanabe, K Maeda, T Ogawa, M Haseyama ITE Technical Report; ITE Tech. Rep. 47 (6), 29-33, 2023 | | 2023 |
クラス情報を導入したグラフ表現による教師有り潜在変数モデルの高精度化に関する検討 渡部航史, 前田圭介, 小川貴弘, 長谷山美紀 映像情報メディア学会技術報告= ITE technical report 47 (6), 29-33, 2023 | | 2023 |
Distributed Label Dequantized Gaussian Process Latent Variable Model for Multi-View Data Integration K Watanabe, K Maeda, T Ogawa, M Haseyama ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | | 2022 |