Publications

Yuki Murakami, Kohsuke Kubota, Takumi Hattori, Keiichi Ochiai (2025). Estimation of Single and Synergistic Treatment Effects under Multiple Treatments with Deep Neural Networks. In KDD 2025 3rd Workshop on Causal Inference and Machine Learning in Practice.

Kohsuke Kubota, Shonosuke Sugasawa (2025). Causal Inference under Threshold Manipulation: A Bayesian Mixture Approach. In KDD 2025 3rd Workshop on Causal Inference and Machine Learning in Practice.

Kohsuke Kubota, Shonosuke Sugasawa, Keiichi Ochiai, Takahiro Hoshino (2025). Bayesian Time-Varying Meta-Analysis via Hierarchical Mean-Variance Random-effects Models. In Japanese Journal of Statistics and Data Science (Impact Factor = 1.0).

Kohsuke Kubota, Keiichi Ochiai, Takahiro Hoshino (2025). Causal effect of lottery promotions on post-win payments: Evidence from a large field experiment . In Innovative Marketing (Impact Factor = 1.2, Acceptance Rate = 33%).

Takumi Hattori, Kohsuke Kubota, Keiichi Ochiai (2025). Wald-Differences-in-Differences Estimation without Individual-Level Treatment Data. In AAAI’25 Workshop on Artificial Intelligence with Causal Techniques.

Hisao Katsumi, Kohsuke Kubota, Wataru Yamada, Keiichi Ochiai (2023). Stay Ahead of the Competition: An Approach for Churn Prediction by Leveraging Competitive Service App Usage Logs. In UbiComp/ISWC ‘23 Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing.

Kohsuke Kubota, Hiroyuki Sato, Wataru Yamada, Keiichi Ochiai, Hiroshi Kawakami (2022). Content-based stock recommendation using smartphone data. In Journal of Information Processing, Specially Selected Paper (top 10%).

Kohsuke Kubota, Keiichi Ochiai (2020). Time-aware GCN: Representation Learning for Mobile App Usage Time-series Data. In KDD 2020 The Second International Workshop on Deep Learning on Graphs:Methods and Applications.