Ryuichiro Hataya

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 29

Top Topics

Image Retrieval

Top Venues

Medical Image Anal.

Publications

Yuka Hashimoto, Ryuichiro Hataya
-algebra Net. CoRR (2024)
Ryuichiro Hataya, Kota Matsui, Masaaki Imaizumi
Automatic Domain Adaptation by Transformers in In-Context Learning. CoRR (2024)
Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Takaaki Mizuno, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Yasuyuki Takamizawa, Yukihiro Yoshida, Satoshi Nakamura, Nobuji Kouno, Amina Bolatkan, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto
Sketch-based semantic retrieval of medical images. Medical Image Anal. 92 (2024)
Ryuichiro Hataya, Yoshinobu Kawahara
Glocal Hypergradient Estimation with Koopman Operator. CoRR (2024)
Han Bao, Ryuichiro Hataya, Ryo Karakida
Self-attention Networks Localize When QK-eigenspectrum Concentrates. CoRR (2024)
Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Mototaka Miyake, Yasuyuki Takamizawa, Sono Ito, Hirokazu Watanabe, Yukihiro Yoshida, Hiroki Yoshimura, Tatsuya Harada, Ryuji Hamamoto
Towards AI-Driven Radiology Education: A Self-supervised Segmentation-Based Framework for High-Precision Medical Image Editing. MICCAI (2) (2023)
Ryuichiro Hataya, Makoto Yamada
Nyström Method for Accurate and Scalable Implicit Differentiation. AISTATS (2023)
Leonardo Placidi, Ryuichiro Hataya, Toshio Mori, Koki Aoyama, Hayata Morisaki, Kosuke Mitarai, Keisuke Fujii
MNISQ: A Large-Scale Quantum Circuit Dataset for Machine Learning on/for Quantum Computers in the NISQ era. CoRR (2023)
Ryuichiro Hataya, Yuka Hashimoto
-algebra. CoRR (2023)
Ryuichiro Hataya, Makoto Yamada
Nystrom Method for Accurate and Scalable Implicit Differentiation. CoRR (2023)
Kazuma Kobayashi, Lin Gu, Ryuichiro Hataya, Takaaki Mizuno, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Yasuyuki Takamizawa, Yukihiro Yoshida, Satoshi Nakamura, Nobuji Kouno, Amina Bolatkan, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto
Sketch-based Medical Image Retrieval. CoRR (2023)
Ryuichiro Hataya, Han Bao, Hiromi Arai
Will Large-scale Generative Models Corrupt Future Datasets? ICCV (2023)
Hiroki Naganuma, Ryuichiro Hataya
An Empirical Investigation of Pre-trained Model Selection for Out-of-Distribution Generalization and Calibration. CoRR (2023)
Ryuichiro Hataya, Hideki Nakayama
DJMix: Unsupervised Task-agnostic Image Augmentation for Improving Robustness of Convolutional Neural Networks. IJCNN (2022)
Ryuichiro Hataya, Han Bao, Hiromi Arai
Will Large-scale Generative Models Corrupt Future Datasets? CoRR (2022)
Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe, Hideki Nakayama
Meta Approach to Data Augmentation Optimization. WACV (2022)
Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Mototaka Miyake, Masamichi Takahashi, Akiko Nakagawa, Tatsuya Harada, Ryuji Hamamoto
Decomposing normal and abnormal features of medical images for content-based image retrieval of glioma imaging. Medical Image Anal. 74 (2021)
Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Mototaka Miyake, Masamichi Takahashi, Akiko Nakagawa, Tatsuya Harada, Ryuji Hamamoto
Decomposing Normal and Abnormal Features of Medical Images into Discrete Latent Codes for Content-Based Image Retrieval. CoRR (2021)
Taiga Kashima, Ryuichiro Hataya, Hideki Nakayama
Visualizing Association in Exemplar-Based Classification. ICASSP (2021)
Ryuichiro Hataya, Hideki Nakayama, Kazuki Yoshizoe
Graph Energy-based Model for Substructure Preserving Molecular Design. CoRR (2021)
Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Tatsuya Harada, Ryuji Hamamoto
Decomposing Normal and Abnormal Features of Medical Images for Content-based Image Retrieval. CoRR (2020)
Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe, Hideki Nakayama
Faster AutoAugment: Learning Augmentation Strategies Using Backpropagation. ECCV (25) (2020)
Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe, Hideki Nakayama
Meta Approach to Data Augmentation Optimization. CoRR (2020)
Kazuma Kobayashi, Ryuichiro Hataya, Yusuke Kurose, Amina Bolatkan, Mototaka Miyake, Hirokazu Watanabe, Masamichi Takahashi, Naoki Mihara, Jun Itami, Tatsuya Harada, Ryuji Hamamoto
Unsupervised Brain Abnormality Detection Using High Fidelity Image Reconstruction Networks. CoRR (2020)
Ryuichiro Hataya, Jan Zdenek, Kazuki Yoshizoe, Hideki Nakayama
Faster AutoAugment: Learning Augmentation Strategies using Backpropagation. CoRR (2019)
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, Giancarlo Mauri
CNN-based Prostate Zonal Segmentation on T2-weighted MR Images: A Cross-dataset Study. CoRR (2019)
Ryuichiro Hataya, Hideki Nakayama
LOL: Learning To Optimize Loss Switching Under Label Noise. ICIP (2019)
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, Giancarlo Mauri, Hideki Nakayama, Paolo Cazzaniga
USE-Net: incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets. CoRR (2019)
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, Giancarlo Mauri, Hideki Nakayama, Paolo Cazzaniga
USE-Net: Incorporating Squeeze-and-Excitation blocks into U-Net for prostate zonal segmentation of multi-institutional MRI datasets. Neurocomputing 365 (2019)