3 citations · 8 across the 13 of their papers we have counts for
7 papers · 1 filter
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…
Exploring Variance Reduction in Importance Sampling for Efficient DNN Training
Takuro Kutsuna
Importance sampling is widely used to improve the efficiency of deep neural network (DNN) training by reducing the variance of gradient estimators. However, efficiently assessing t…
One-Shot Domain Incremental Learning
Yasushi Esaki, Satoshi Koide, Takuro Kutsuna
Domain incremental learning (DIL) has been discussed in previous studies on deep neural network models for classification. In DIL, we assume that samples on new domains are observe…
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…
Supervised Contrastive Learning with Heterogeneous Similarity for Distribution Shifts
Takuro Kutsuna
Distribution shifts are problems where the distribution of data changes between training and testing, which can significantly degrade the performance of a model deployed in the rea…
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…