A Binary Decision Diagram-Based One-Class Classifier. - Takuro Kutsuna (ICDM, 2010)

Efficient Root Cause Detection in Complex Embedded Systems with Abstract Model-based Diagnosis. - Takuro Kutsuna; Shuichi Sato; Naoya Chujo (J. Inf. Process., 2012)

Hybrid Systems: Theory and Practice, Seriously (NII Shonan Meeting 2012-2). - Ichiro Hasuo; Takuro Kutsuna; Toshimitsu Ushio (NII Shonan Meet. Rep., 2012)

Outlier Detection Based on Leave-One-Out Density Using Binary Decision Diagrams. - Takuro Kutsuna; Akihiro Yamamoto (PAKDD (2), 2014)

A parameter-free approach for one-class classification using binary decision diagrams. - Takuro Kutsuna; Akihiro Yamamoto (Intell. Data Anal., 2014)

Enhancing System Reliability using Abstraction and Efficient Logical Computation. - Takuro Kutsuna (2015)

Analyzing Unsatisfiability in Bounded Model Checking Using Max-SMT and Dual Slicing. - Takuro Kutsuna; Yoshinao Ishii (FMICS-AVoCS, 2016)

Effective Fault Localization Using Dynamic Slicing and an SMT Solver. - Yoshinao Ishii; Takuro Kutsuna (ICST Workshops, 2016)

Abstraction and refinement of mathematical functions toward SMT-based test-case generation. - Takuro Kutsuna; Yoshinao Ishii; Akihiro Yamamoto (Int. J. Softw. Tools Technol. Transf., 2016)

Outlier detection using binary decision diagrams. - Takuro Kutsuna; Akihiro Yamamoto (Data Min. Knowl. Discov., 2017)

Neural Edit Operations for Biological Sequences. - Satoshi Koide; Keisuke Kawano; Takuro Kutsuna (NeurIPS, 2018)

Canonical Soft Time Warping. - Keisuke Kawano; Satoshi Koide; Takuro Kutsuna (ACML, 2019)

Flow-based Image-to-Image Translation with Feature Disentanglement. - Ruho Kondo; Keisuke Kawano; Satoshi Koide; Takuro Kutsuna (NeurIPS, 2019)

Linearly Constrained Weights: Reducing Activation Shift for Faster Training of Neural Networks. - Takuro Kutsuna (ECML/PKDD (2), 2019)

Learning Wasserstein Isometric Embedding for Point Clouds. - Keisuke Kawano; Satoshi Koide; Takuro Kutsuna (3DV, 2020)

Neural Time Warping for Multiple Sequence Alignment. - Keisuke Kawano; Takuro Kutsuna; Satoshi Koide (ICASSP, 2020)

Finding Misdetections in Unlabeled Image Database: Toward Reliable Object Detection. - Satoshi Koide; Keisuke Kawano; Akihiro Nakamura; Takuro Kutsuna; Naoki Mitsumoto (ITSC, 2021)

Understanding the Reason for Misclassification by Generating Counterfactual Images. - Muneaki Suzuki; Yoshitaka Kameya; Takuro Kutsuna; Naoki Mitsumoto (MVA, 2021)

Supervised Contrastive Learning with Heterogeneous Similarity for Distribution Shifts. - Takuro Kutsuna (CoRR, 2023)

StyleDiff: Attribute comparison between unlabeled datasets in latent disentangled space. - Keisuke Kawano; Takuro Kutsuna; Ryoko Tokuhisa; Akihiro Nakamura; Yasushi Esaki (Image Vis. Comput., 2023)

Accuracy-Preserving Calibration via Statistical Modeling on Probability Simplex. - Yasushi Esaki; Akihiro Nakamura; Keisuke Kawano; Ryoko Tokuhisa; Takuro Kutsuna (AISTATS, 2024)

One-Shot Domain Incremental Learning. - Yasushi Esaki; Satoshi Koide; Takuro Kutsuna (IJCNN, 2024)

How many views does your deep neural network use for prediction? - Keisuke Kawano; Takuro Kutsuna; Keisuke Sano (CoRR, 2024)

Generalized Diffusion Model with Adjusted Offset Noise. - Takuro Kutsuna (CoRR, 2024)

Minimal sufficient views: A DNN model making predictions with more evidence has higher accuracy. - Keisuke Kawano; Takuro Kutsuna; Keisuke Sano (Neural Networks, 2025)

Exploring Variance Reduction in Importance Sampling for Efficient DNN Training. - Takuro Kutsuna (CoRR, 2025)

An Asymptotic Equation Linking WAIC and WBIC in Singular Models. - Naoki Hayashi; Takuro Kutsuna; Sawa Takamuku (CoRR, 2025)

CT-OT Flow: Estimating Continuous-Time Dynamics from Discrete Temporal Snapshots. - Keisuke Kawano; Takuro Kutsuna; Naoki Hayashi; Yasushi Esaki; Hidenori Tanaka (CoRR, 2025)