24 papers
AdaKoop: Efficient Modeling of Nonlinear Dynamics from Nonstationary Data Streams with Koopman Operator Regression
Naoki Chihara, Ren Fujiwara, Yasuko Matsubara +1
Real-time data analysis requires the ability to accurately and adaptively address nonlinear dynamics in a nonstationary data stream while preserving computational efficiency. Howev…
Modeling Covariate Transition for Efficient Estimation of Longitudinal Treatment Effects in Randomized Experiments
Naoki Chihara, Tatsushi Oka, Yasuko Matsubara +2
We present a regression-adjustment framework designed for the estimation of longitudinal treatment effects in randomized experiments under static regimes. While regression-adjustme…
Modeling Dynamic Mixtures of Time-Delay Systems from Streaming Time Series
Ren Fujiwara, Yasuko Matsubara, Yasushi Sakurai
This research addresses the problem of adaptive modeling in time-series data streams with clear input-output relationships. This problem is challenging because rapid system changes…
When to Retrain after Drift: A Data-Only Test of Post-Drift Data Size Sufficiency
Ren Fujiwara, Yasuko Matsubara, Yasushi Sakurai
Sudden concept drift makes previously trained predictors unreliable, yet deciding when to retrain and what post-drift data size is sufficient is rarely addressed. We propose CALIPE…
EpiGraph: Building Generalists for Evidence-Intensive Epilepsy Reasoning in the Wild
Yuyang Dai, Zheng Chen, Jathurshan Pradeepkumar +4
Epilepsy diagnosis and treatment require evidence-intensive reasoning across heterogeneous clinical knowledge, including biosignal patterns, genetic mechanisms, pharmacogenomics, t…
ExPath: Targeted Pathway Inference for Biological Knowledge Bases via Graph Learning and Explanation
Rikuto Kotoge, Ziwei Yang, Zheng Chen +4
Retrieving targeted pathways in biological knowledge bases, particularly when incorporating wet-lab experimental data, remains a challenging task and often requires downstream anal…