| 2025 | ICONIP | SAPAG: Self-attention Parts Guidance with Latent Diffusion Models for Anomaly Detection in Microscopy Images. | Kazuki Shimizu, Yukako Tohsato |
| 2022 | ICANN | Phenotype Anomaly Detection for Biological Dynamics Data Using a Deep Generative Model. | Eisuke Ito, Takaya Ueda, Ryo Takano, Yukako Tohsato, Koji Kyoda, Shuichi Onami, Ikuko Nishikawa |
| 2022 | ICANN | Unsupervised Domain Adaptation Using Temporal Association for Segmentation and Its Application to C. elegans Time-Lapse Images. | Hiroaki Nozaki, Yukako Tohsato |
| 2020 | ICANN | Temporal Anomaly Detection by Deep Generative Models with Applications to Biological Data. | Takaya Ueda, Yukako Tohsato, Ikuko Nishikawa |
| 2019 | ICNC | Characterizing Phenotype Abnormality by Variational Auto Encoder. | Yuki Kimura, Takaya Ueda, Seo Masataka, Yukako Tohsato, Ikuko Nishikawa |
| 2019 | ICNC | Analysis of Time Series Anomalies Using Causal InfoGAN and Its Application to Biological Data. | Takaya Ueda, Masataka Seo, Yukako Tohsato, Ikuko Nishikawa |
| 2003 | DASFAA | Clustering Method for Comparative Analysis between Genomes and Pathways. | Shoko Miyake, Yukako Tohsato, Yoichi Takenaka, Hideo Matsuda |
| 2000 | ISMB | A Multiple Alignment Algorithm for Metabolic Pathway Analysis Using Enzyme Hierarchy. | Yukako Tohsato, Hideo Matsuda, Akihiro Hashimoto |