ジャーナル論文 / Journal
- Takeuchi, I., "Statistical Reliability of Data-driven Science and Technology", IEEJ Trans. Electr. Electron. Eng., (2025).
- Shiraishi, T., Miwa, D., Le Duy, V. N., and Takeuchi, I., "Selective Inference for Change Point Detection by Recurrent Neural Network", Neural Comput. 37(1), 160–192, (2024).
- Shiraishi, T., Miwa, D., Duy, V. N., and Takeuchi, I., "Bounded p values in parametric programming-based selective inference", Journal of the Japan Statistical Society 7(2), 633–665, (2024).
- Kutsukake, K., Kamioka, T., Matsui, K., Takeuchi, I., Segi, T., Sasaki, T., Fujikawa, S., and Takahasi, M., "Feature extraction and spatial imaging of synchrotron radiation X-ray diffraction patterns using unsupervised machine learning", Science and Technology of Advanced Materials Methods 4(1), 2336402, (2024).
- Koga, R., Koide, S., Tanaka, H., Taguchi, K., Kugler, M., Yokota, T., Ohshima, K., Miyoshi, H., Nagaishi, M., Hashimoto, N., Takeuchi, I., and Hontani, H., "A study of criteria for grading follicular lymphoma using a cell type classifier from pathology images based on complementary-label learning", Micron 184, 103663, (2024).
- Inatsu, Y., Takeno, S., Kutsukake, K., and Takeuchi, I., "Active Learning for Level Set Estimation Using Randomized Straddle Algorithms", Transactions on Machine Learning Research, (2024).
- CUI, Y., TAKEUCHI, I., YANG, W., Shaojie , G., YOON, S., and MATSUMOTO, T., "Artificial neural network to predict the structural compliance of irregular geometries considering volume constraints.", Mechanical Engineering Journal , (2024).
- Bunker, R., Vo, L. N., Tabei, Y., Takeuchi, I., and Fujii, K., "Multi-agent statistical discriminative sub-trajectory mining and an application to NBA basketball.", Journal of Quantitative Analysis in Sports, (2024).
- Bunker, R., Le Duy, V., Tabei, Y., Takeuchi, I., and Fujii, K., "Multi-agent statistically discriminative sub-trajectory mining and an application to NBA basketball", Journal of Quantitative Analysis in Sports, (2024).
- Boyar, O., and Takeuchi, I., "Latent Space Bayesian Optimization With Latent Data Augmentation for Enhanced Exploration", Neural Comput. 36(11), 2446–2478, (2024).
- Yoshida, T., Hanada, H., Nakagawa, K., Taji, K., Tsuda, K., and Takeuchi, I., "Efficient model selection for predictive pattern mining model by safe pattern pruning", Patterns 4(12), 100890, (2023).
- Yamaguchi, Y., Atsumi, T., Kanamori, K., Tanibata, N., Takeda, H., Nakayama, M., Karasuyama, M., and Takeuchi, I., "Drawing a materials map with an autoencoder for lithium ionic conductors", Sci. Rep. 13(1), 16799, (2023).
- Takagi, Y., Hashimoto, N., Masuda, H., Miyoshi, H., Ohshima, K., Hontani, H., and Takeuchi, I., "Transformer-based personalized attention mechanism for medical images with clinical records", Journal of Pathology Informatics 14, (2023).
- Nagaishi, M., Miyoshi, H., Kugler, M., Sato, K., Kohno, K., Takeuchi, M., Yamada, K., Furuta, T., Hashimoto, N., Takeuchi, I., Hontani, H., and Ohshima, K., "The Detection of Neoplastic Cells Using Objective Cytomorphologic Parameters in Malignant Lymphoma", Lab. Invest. 104(3), 100302, (2023).
- Hiroyuki, H., Hashimoto, N., Taji, K., and Takeuchi, I., "Generalized Low-Rank Update: Model Parameter Bounds for Low-Rank Training Data Modifications", Neural Comput. 35(12), 1970–2005, (2023).
- Hashimoto, N., Takagi, Y., Masuda, H., Miyoshi, H., Kohno, K., Nagaishi, M., Sato, K., Takeuchi , M., Furuta, T., Kawamoto, K., Yamada, K., Moritsubo, M., Inoue, K., Shimasaki, Y., Ogura, Y., Imamoto, T., Mishina, T., Tanaka, K., Kawaguchi, Y., Nakamura, S., Ohshima, K., Hontani, H., and Takeuchi, I., "Case-based similar image retrieval for weakly annotated large histopathological images of malignant lymphoma using deep metric learning", Med. Image Anal. 85, (2023).
- Hashimoto, N., Hanada, H., Miyoshi, H., Nagaishi, M., Sato, K., Hontani, H., Ohshima, K., and Takeuchi, I., "Multimodal Gated Mixture of Experts Using Whole Slide Image and Flow Cytometry for Multiple Instance Learning Classification of Lymphoma", Journal of Pathology Informatics, 100359, (2023).
- Goto, K., Tamehiro, N., Yoshida, T., Hanada, H., Sakuma, T., Adachi, R., Kondo, K., and Takeuchi, I., "Novel machine learning method allerStat identifies statistically significant allergen-specific patterns in protein sequences", J. Biol. Chem. 299(6), 104733, (2023).
- Fuse, Y., Takeuchi, K., Hashimoto, N., Nagata, Y., Takagi, Y., Nagatani, T., Takeuchi, I., and Saito, R., "Deep learning based identification of pituitary adenoma on surgical endoscopic images: a pilot study", Neurosurg. Rev. 46(1), 291, (2023).
- Suzuki, K., Tange, M., Yamagishi, R., Hanada, H., Mukai, S., Sato, T., Tanaka, T., Akashi, T., Kadomatsu, K., Maeda, T., Miida, T., Takeuchi, I., Murakami, H., Sekido, Y., and Murakami-Tonami, Y., "SMG6 regulates DNA damage and cell survival in Hippo pathway kinase LATS2-inactivated malignant mesothelioma", Cell Death Discovery 8(1), (2022).
- Hashimoto, N., Ko, K., Yokota, T., Kohno, K., Nakaguro, M., Nakamura, S., Takeuchi, I., and Hontani, H., "Subtype classification of malignant lymphoma using immunohistochemical staining pattern", International Journal of Computer Assisted Radiology and Surgery, (2022).
国際会議 / Proceedings
- Onoki, J., Tsuchimoto, Y., Yokota, T., Ohshima, K., Miyoshi , H., Hashimoto, N., Takeuchi, I., and Hontani, H., "Construction of a Pathology Image Classifier with Quantifiable Uncertainty Evaluation for Cancer Diagnosis Assistance", International Forum on Medical Imaging in Asia, (2025).
- Koga, R., Yokota, T., Ohshima, K., Miyoshi, H., Hashimoto, N., Takeuchi, I., and Hontani, H., "Generation of Counterfactual Pathology Images of Malignant Lymphoma using Diffusion Models", International Forum on Medical Imaging in Asia, (2025).
- Kawakami, S., Hashimoto, N., Miyoshi, H., Sakuma, J., Hontani, H., and Takeuchi, I., "Machine Learning for Classifying and Generating Videos of Pathological Image Observation Process", International Forum on Medical Imaging in Asia, (2025).
- Takeno, S., Inatsu, Y., Karasuyama, M., and Takeuchi, I., "Posterior Sampling-Based Bayesian Optimization with Tighter Bayesian Regret Bounds", Proceedings of The 41th International Conference on Machine Learning, (2024).
- Shiraishi , T., Miwa, D., Katsuoka, T., Le Duy, V. N., Taji, K., and Takeuchi , I., "Statistical Test for Attention Maps in Vision Transformers", Proceedings of The 41th International Conference on Machine Learning, (2024).
- Ozaki, R., Ishikawa, K., Kanzaki, Y., Suzuki, S., Takeno, S., Takeuchi, I., and Karasuyama, M., "Multi-objective Bayesian Optimization with Active Preference Learning", Proceedings of the 38th AAAI Conference on Artificial Intelligence, (2024).
- Le Duy, V. N., Lin, H., and Takeuchi, I., "CAD-DA: Controllable Anomaly Detection after Domain Adaptation by Statistical Inference", AI&Statistics, (2024).
- Iwazaki, S., Tanabe, T., Irie, M., Takeno, S., and Inatsu, Y., "Risk Seeking Bayesian Optimization under Uncertainty for Obtaining Extremum", Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, (2024).
- Inatsu, Y., Takeno, S., Hanada, H., Iwata, K., and Takeuchi, I., "Bounding Box-based Multi-objective Bayesian Optimization of Risk Measures under Input Uncertainty", Proceedings of the 27th International Conference on Artificial Intelligence and Statistics, (2024).
- Takeno, S., Nomura, M., and Karasuyama, M., "Towards Practical Preferential Bayesian Optimization with Skew Gaussian Processes", Proceedings of the 40th International Conference on Machine Learning (ICML) 202, 33516–33533, (2023).
- Takeno, S., Inatsu, Y., and Karasuyama, M., "Randomized Gaussian Process Upper Confidence Bound with Tighter Bayesian Regret Bounds", Proceedings of the 40th International Conference on Machine Learning (ICML) 202, 33490–33515, (2023).
- Iwazaki, S., Takeno, S., Tanabe, T., and Mitsuru, I., "Failure-Aware Gaussian Process Optimization with Regret Bounds", Proceedings of Advances in Neural Information Processing Systems 36 , (2023).
- Das, D., Vo, D. N., and Takeuchi, I., "Fast and More Powerful Selective Inference for Sparse High-order Interaction Model", Proceedings of AAAI Conference on Artificial Intelligence (AAAI2022), (2022).
- Vo, D. N., and Takeuchi, I., "Parametric Programming Approach for More Powerful and General Lasso Selective Inference", Proceedings of The 24th International Conference on Artifical Intelligence and Statistics (AISTATS2021), (2021).
- Sugiyama, K., Vo, D. N., and Takeuchi, I., "More Powerful and General Selective Inference for Stepwise Feature Selection using Homotopy Method", Proceedings of International Conference on Machine Learning 2021 (ICML2021), (2021).
- Iwazaki, S., Inatsu, Y., and Takeuchi, I., "Mean-Variance Analysis in Bayesian Optimization under Uncertainty", Proceedings of The 24th International Conference on Artifical Intelligence and Statistics (AISTATS2021), (2021).
- Inatsu, Y., Iwazaki, S., and Takeuchi, I., "Active Learning for Distributionally Robust Level-Set Estimation", Proceedings of International Conference on Machine Learning 2021 (ICML2021), (2021).