LOL: Learning To Optimize Loss Switching Under Label Noise. - Ryuichiro Hataya; Hideki Nakayama (ICIP, 2019)

CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study. - Leonardo Rundo; Changhee Han; Jin Zhang; Ryuichiro Hataya; Yudai Nagano; Carmelo Militello; Claudio Ferretti; Marco S. Nobile; Andrea Tangherloni; Maria Carla Gilardi; Salvatore Vitabile; Hideki Nakayama; et al. (CoRR, 2019)

USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets. - Leonardo Rundo; Changhee Han; Yudai Nagano; Jin Zhang; Ryuichiro Hataya; Carmelo Militello; Andrea Tangherloni; Marco S. Nobile; Claudio Ferretti; Daniela Besozzi; Maria Carla Gilardi; Salvatore Vitabile; et al. (Neurocomputing, 2019)

Faster AutoAugment: Learning Augmentation Strategies Using Backpropagation. - Ryuichiro Hataya; Jan Zdenek; Kazuki Yoshizoe; Hideki Nakayama (ECCV (25), 2020)

Unsupervised Brain Abnormality Detection Using High Fidelity Image Reconstruction Networks. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Amina Bolatkan; Mototaka Miyake; Hirokazu Watanabe; Masamichi Takahashi; Naoki Mihara; Jun Itami; Tatsuya Harada; Ryuji Hamamoto (CoRR, 2020)

Decomposing Normal and Abnormal Features of Medical Images for Content-based Image Retrieval. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Tatsuya Harada; Ryuji Hamamoto (CoRR, 2020)

CNN-Based Prostate Zonal Segmentation on T2-Weighted MR Images: A Cross-Dataset Study. - Leonardo Rundo; Changhee Han; Jin Zhang; Ryuichiro Hataya; Yudai Nagano; Carmelo Militello; Claudio Ferretti; Marco S. Nobile; Andrea Tangherloni; Maria Carla Gilardi; Salvatore Vitabile; Hideki Nakayama; et al. (Neural Approaches to Dynamics of Signal Exchanges, 2020)

Visualizing Association in Exemplar-Based Classification. - Taiga Kashima; Ryuichiro Hataya; Hideki Nakayama (ICASSP, 2021)

Graph Energy-based Model for Substructure Preserving Molecular Design. - Ryuichiro Hataya; Hideki Nakayama; Kazuki Yoshizoe (CoRR, 2021)

Decomposing Normal and Abnormal Features of Medical Images into Discrete Latent Codes for Content-Based Image Retrieval. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Mototaka Miyake; Masamichi Takahashi; Akiko Nakagawa; Tatsuya Harada; Ryuji Hamamoto (CoRR, 2021)

Decomposing normal and abnormal features of medical images for content-based image retrieval of glioma imaging. - Kazuma Kobayashi; Ryuichiro Hataya; Yusuke Kurose; Mototaka Miyake; Masamichi Takahashi; Akiko Nakagawa; Tatsuya Harada; Ryuji Hamamoto (Medical Image Anal., 2021)

DJMix: Unsupervised Task-agnostic Image Augmentation for Improving Robustness of Convolutional Neural Networks. - Ryuichiro Hataya; Hideki Nakayama (IJCNN, 2022)

Meta Approach to Data Augmentation Optimization. - Ryuichiro Hataya; Jan Zdenek; Kazuki Yoshizoe; Hideki Nakayama (WACV, 2022)

Nyström Method for Accurate and Scalable Implicit Differentiation. - Ryuichiro Hataya; Makoto Yamada (AISTATS, 2023)

Will Large-scale Generative Models Corrupt Future Datasets? - Ryuichiro Hataya; Han Bao 002; Hiromi Arai (ICCV, 2023)

Towards AI-Driven Radiology Education: A Self-supervised Segmentation-Based Framework for High-Precision Medical Image Editing. - Kazuma Kobayashi; Lin Gu 003; Ryuichiro Hataya; Mototaka Miyake; Yasuyuki Takamizawa; Sono Ito; Hirokazu Watanabe; Yukihiro Yoshida; Hiroki Yoshimura; Tatsuya Harada; Ryuji Hamamoto (MICCAI (2), 2023)

Noncommutative C*-algebra Net: Learning Neural Networks with Powerful Product Structure in C*-algebra. - Ryuichiro Hataya; Yuka Hashimoto (CoRR, 2023)

Sketch-based Medical Image Retrieval. - Kazuma Kobayashi; Lin Gu 003; Ryuichiro Hataya; Takaaki Mizuno; Mototaka Miyake; Hirokazu Watanabe; Masamichi Takahashi; Yasuyuki Takamizawa; Yukihiro Yoshida; Satoshi Nakamura; Nobuji Kouno; Amina Bolatkan; et al. (CoRR, 2023)

MNISQ: A Large-Scale Quantum Circuit Dataset for Machine Learning on/for Quantum Computers in the NISQ era. - Leonardo Placidi; Ryuichiro Hataya; Toshio Mori; Koki Aoyama; Hayata Morisaki; Kosuke Mitarai; Keisuke Fujii 004 (CoRR, 2023)

An Empirical Investigation of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration. - Hiroki Naganuma; Ryuichiro Hataya (CoRR, 2023)

Self-attention Networks Localize When QK-eigenspectrum Concentrates. - Han Bao 002; Ryuichiro Hataya; Ryo Karakida (ICML, 2024)

Glocal Hypergradient Estimation with Koopman Operator. - Ryuichiro Hataya; Yoshinobu Kawahara (CoRR, 2024)

Quantum Circuit C*-algebra Net. - Yuka Hashimoto; Ryuichiro Hataya (CoRR, 2024)

Automatic Domain Adaptation by Transformers in In-Context Learning. - Ryuichiro Hataya; Kota Matsui; Masaaki Imaizumi (CoRR, 2024)

Sketch-based semantic retrieval of medical images. - Kazuma Kobayashi; Lin Gu 003; Ryuichiro Hataya; Takaaki Mizuno; Mototaka Miyake; Hirokazu Watanabe; Masamichi Takahashi; Yasuyuki Takamizawa; Yukihiro Yoshida; Satoshi Nakamura; Nobuji Kouno; Amina Bolatkan; et al. (Medical Image Anal., 2024)

An Empirical Study of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration. - Hiroki Naganuma; Ryuichiro Hataya; Kotaro Yoshida; Ioannis Mitliagkas (Trans. Mach. Learn. Res., 2025)