Research
研究
研究業績
カテゴリー
研究領域
年
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Quantization-Aware Diffusion Models For Maximum Likelihood Training
Shohei Taniguchi, Masahiro Suzuki, Yutaka Matsuo
International Conference on Learning Representations 2026 (ICLR2026), April 2026
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One-shot Portrait Stylizaiton via Geometric Alignment
Xinrui Wang, Zilin Guo, Zhuoru Li, Jinze Yu, Heng Zhang, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo
Proceedings of The IEEE/CVF Winter Conference on Applications of Computer Vision 2026 (WACV2026), March 2026.
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Pairwise Optimal Transports for Training All-to-All Flow-Based Condition Transfer Model
Kotaro Ikeda, Masanori Koyama, Jinzhe Zhang, Kohei Hayashi, Kenji Fukumizu
Advances in Neural Information Processing Systems 38 (NeurIPS 2025), December 2025.
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パーソナライズ画像生成における参照画像の複製効果の定量的評価と改善
大坂洋豊, 鈴木雅大, 松尾豊
情報処理学会論文誌, 2025
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Inference-Time Text-to-Video Alignment with Diffusion Latent Beam Search
Yuta Oshima, Masahiro Suzuki, Yutaka Matsuo, Hiroki Furuta.
Advances in Neural Information Processing Systems (NeurIPS 2025), December 2025
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Efficient Object-Centric Representation Learning using Masked Generative Modeling
Akihiro Nakano, Masahiro Suzuki, Yutaka Matsuo
Transactions on Machine Learning Research (TMLR), 2025
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The Geometry of Phase Transitions in Diffusion Models: Tubular Neighbourhoods and Singularities
Manato Yaguchi*, Kotaro Sakamoto*, Ryosuke Sakamoto*, Masato Tanabe*, Masatomo Akagawa*, Yusuke Hayashi*, Masahiro Suzuki, Yutaka Matsuo (*Equal Contribution)
Transactions on Machine Learning Research (TMLR), 2025
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ガウス過程潜在変数モデルとニューラルネットワークの統合によるマルチエージェント記号創発と潜在表現学習
中村友昭, 鈴木雅大, 谷口彰, 谷口忠大
日本ロボット学会誌（レター）, (2024)
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Pixyz: a Python library for developing deep generative models
Masahiro Suzuki, Takaaki Kaneko, Yutaka Matsuo: Pixyz
Advanced Robotics, (2023)
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Learning Global Spatial Information for Multi-View Object-Centric Models
Yuya Kobayashi, Masahiro Suzuki, Yutaka Matsuo
Advanced Robotics, (2023).