1 citations · 2 across the 8 of their papers we have counts for
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CT-OT Flow: Estimating Continuous-Time Dynamics from Discrete Temporal Snapshots
Keisuke Kawano, Takuro Kutsuna, Naoki Hayashi +2
In many real-world settings--e.g., single-cell RNA sequencing, mobility sensing, and environmental monitoring--data are observed only as temporally aggregated snapshots collected o…
Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex
Yasushi Esaki, Akihiro Nakamura, Keisuke Kawano +2
Classification models based on deep neural networks (DNNs) must be calibrated to measure the reliability of predictions. Some recent calibration methods have employed a probabilist…
Minimal Sufficient Views: A DNN model making predictions with more evidence has higher accuracy
Keisuke Kawano, Takuro Kutsuna, Keisuke Sano
Deep neural networks (DNNs) exhibit high performance in image recognition; however, the reasons for their strong generalization abilities remain unclear. A plausible hypothesis is…
Partial Wasserstein Covering
Keisuke Kawano, Satoshi Koide, Keisuke Otaki
We consider a general task called partial Wasserstein covering with the goal of providing information on what patterns are not being taken into account in a dataset (e.g., dataset…
Neural Time Warping For Multiple Sequence Alignment
Keisuke Kawano, Takuro Kutsuna, Satoshi Koide
Multiple sequences alignment (MSA) is a traditional and challenging task for time-series analyses. The MSA problem is formulated as a discrete optimization problem and is typically…