activity
20202025
most citedVariational Monocular Depth Estimation for Reliability Prediction

1 citations · 2 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2025

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…

cs.LG2024

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…

cs.LG2024★ 1 cited

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…

stat.ML2023

StyleDiff: Attribute Comparison Between Unlabeled Datasets in Latent Disentangled Space

Keisuke Kawano, Takuro Kutsuna, Ryoko Tokuhisa +2

One major challenge in machine learning applications is coping with mismatches between the datasets used in the development and those obtained in real-world applications. These mis…

cs.LG2021

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…

cs.CV2020★ 1 cited

Variational Monocular Depth Estimation for Reliability Prediction

Noriaki Hirose, Shun Taguchi, Keisuke Kawano +1

Self-supervised learning for monocular depth estimation is widely investigated as an alternative to supervised learning approach, that requires a lot of ground truths. Previous wor…

cs.LG2020

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…

cs.CV2020

PLG-IN: Pluggable Geometric Consistency Loss with Wasserstein Distance in Monocular Depth Estimation

Noriaki Hirose, Satoshi Koide, Keisuke Kawano +1

We propose a novel objective for penalizing geometric inconsistencies to improve the depth and pose estimation performance of monocular camera images. Our objective is designed usi…