| 2026 | AAAI | Difference Vector Equalization for Robust Fine-tuning of Vision-Language Models. | Satoshi Suzuki, Shin'ya Yamaguchi, Shoichiro Takeda, Taiga Yamane, Naoki Makishima, Naotaka Kawata, Mana Ihori, Tomohiro Tanaka, Shota Orihashi, Ryo Masumura |
| 2026 | WACV | Distribution Highlighted Reference-based Label Distribution Learning for Facial Age Estimation. | Satoshi Suzuki, Shin'ya Yamaguchi, Shoichiro Takeda, Takuhiro Kaneko, Shota Orihashi, Ryo Masumura |
| 2025 | AAAI | Explanation Bottleneck Models. | Shin'ya Yamaguchi, Kosuke Nishida |
| 2025 | CVPR | Post-pre-training for Modality Alignment in Vision-Language Foundation Models. | Shin'ya Yamaguchi, Dewei Feng, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa |
| 2025 | ICLR | Test-time Adaptation for Regression by Subspace Alignment. | Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai, Tomoki Hamagami |
| 2025 | IJCNN | Evaluation of Time-Series Training Dataset through Lens of Spectrum of Deep State Space Models. | Sekitoshi Kanai, Yasutoshi Ida, Kazuki Adachi, Mihiro Uchida, Tsukasa Yoshida, Shin'ya Yamaguchi |
| 2024 | ACML | Toward Data Efficient Model Merging between Different Datasets without Performance Degradation. | Masanori Yamada, Tomoya Yamashita, Shin'ya Yamaguchi, Daiki Chijiwa |
| 2024 | ACML | Analyzing Diffusion Models on Synthesizing Training Datasets. | Shin'ya Yamaguchi |
| 2024 | CVPR | Adaptive Random Feature Regularization on Fine-tuning Deep Neural Networks. | Shin'ya Yamaguchi, Sekitoshi Kanai, Kazuki Adachi, Daiki Chijiwa |
| 2024 | IJCNN | Test-time Similarity Modification for Person Re-identification toward Temporal Distribution Shift. | Kazuki Adachi, Shohei Enomoto, Taku Sasaki, Shin'ya Yamaguchi |
| 2024 | IJCNN | Test-time Adaptation Meets Image Enhancement: Improving Accuracy via Uncertainty-aware Logit Switching. | Shohei Enomoto, Naoya Hasegawa, Kazuki Adachi, Taku Sasaki, Shin'ya Yamaguchi, Satoshi Suzuki, Takeharu Eda |
| 2023 | ACML | Generative Semi-supervised Learning with Meta-Optimized Synthetic Samples. | Shin'ya Yamaguchi |
| 2023 | ICCV | Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff. | Satoshi Suzuki, Shin'ya Yamaguchi, Shoichiro Takeda, Sekitoshi Kanai, Naoki Makishima, Atsushi Ando, Ryo Masumura |
| 2023 | ICIP | Covariance-Aware Feature Alignment with Pre-Computed Source Statistics for Test-Time Adaptation to Multiple Image Corruptions. | Kazuki Adachi, Shin'ya Yamaguchi, Atsutoshi Kumagai |
| 2023 | ICML | One-vs-the-Rest Loss to Focus on Important Samples in Adversarial Training. | Sekitoshi Kanai, Shin'ya Yamaguchi, Masanori Yamada, Hiroshi Takahashi, Kentaro Ohno, Yasutoshi Ida |
| 2021 | ICCV | F-Drop&Match: GANs with a Dead Zone in the High-Frequency Domain. | Shin'ya Yamaguchi, Sekitoshi Kanai |
| 2021 | ICIP | Image Enhanced Rotation Prediction for Self-Supervised Learning. | Shin'ya Yamaguchi, Sekitoshi Kanai, Tetsuya Shioda, Shoichiro Takeda |
| 2021 | IJCNN | Constraining Logits by Bounded Function for Adversarial Robustness. | Sekitoshi Kanai, Masanori Yamada, Shin'ya Yamaguchi, Hiroshi Takahashi, Yasutoshi Ida |
| 2020 | AAAI | Effective Data Augmentation with Multi-Domain Learning GANs. | Shin'ya Yamaguchi, Sekitoshi Kanai, Takeharu Eda |
| 2017 | ACIIDS | A Fusion Technique of Schema and Syntax Rules for Validating Open Data. | Shin'ya Yamaguchi, Kimio Kuramitsu |