Uesaka, Toshimitsu

16 publications

ICLR 2026 Improved Object-Centric Diffusion Learning with Registers and Contrastive Alignment Bac Nguyen, Yuhta Takida, Naoki Murata, Chieh-Hsin Lai, Toshimitsu Uesaka, Stefano Ermon, Yuki Mitsufuji

ICLR 2026 SONA: Learning Conditional, Unconditional, and Matching-Aware Discriminator Yuhta Takida, Satoshi Hayakawa, Takashi Shibuya, Masaaki Imaizumi, Naoki Murata, Bac Nguyen, Toshimitsu Uesaka, Chieh-Hsin Lai, Yuki Mitsufuji

TMLR 2025 G2D2: Gradient-Guided Discrete Diffusion for Inverse Problem Solving Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Bac Nguyen, Stefano Ermon, Yuki Mitsufuji

ICLRW 2025 Improving Vector-Quantized Image Modeling with Latent Consistency-Matching Diffusion Bac Nguyen, Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Stefano Ermon, Yuki Mitsufuji

ICLR 2025 Weighted Point Set Embedding for Multimodal Contrastive Learning Toward Optimal Similarity Metric Toshimitsu Uesaka, Taiji Suzuki, Yuhta Takida, Chieh-Hsin Lai, Naoki Murata, Yuki Mitsufuji

ICLR 2024 Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Naoki Murata, Yuhta Takida, Toshimitsu Uesaka, Yutong He, Yuki Mitsufuji, Stefano Ermon

NeurIPSW 2024 Disentangling Multi-Instrument Music Audio for Source-Level Pitch and Timbre Manipulation Yin-Jyun Luo, Kin Wai Cheuk, Woosung Choi, Wei-Hsiang Liao, Keisuke Toyama, Toshimitsu Uesaka, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Simon Dixon, Yuki Mitsufuji

TMLR 2024 HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes Yuhta Takida, Yukara Ikemiya, Takashi Shibuya, Kazuki Shimada, Woosung Choi, Chieh-Hsin Lai, Naoki Murata, Toshimitsu Uesaka, Kengo Uchida, Wei-Hsiang Liao, Yuki Mitsufuji

ICLR 2024 Manifold Preserving Guided Diffusion Yutong He, Naoki Murata, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Dongjun Kim, Wei-Hsiang Liao, Yuki Mitsufuji, J Zico Kolter, Ruslan Salakhutdinov, Stefano Ermon

NeurIPS 2024 PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher Dongjun Kim, Chieh-Hsin Lai, Wei-Hsiang Liao, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICLR 2024 SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya, Chieh-Hsin Lai, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji

ICML 2023 FP-Diffusion: Improving Score-Based Diffusion Models by Enforcing the Underlying Score Fokker-Planck Equation Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICML 2023 GibbsDDRM: A Partially Collapsed Gibbs Sampler for Solving Blind Inverse Problems with Denoising Diffusion Restoration Naoki Murata, Koichi Saito, Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICMLW 2023 On the Equivalence of Consistency-Type Models: Consistency Models, Consistent Diffusion Models, and Fokker-Planck Regularization Chieh-Hsin Lai, Yuhta Takida, Toshimitsu Uesaka, Naoki Murata, Yuki Mitsufuji, Stefano Ermon

NeurIPSW 2022 Regularizing Score-Based Models with Score Fokker-Planck Equations Chieh-Hsin Lai, Yuhta Takida, Naoki Murata, Toshimitsu Uesaka, Yuki Mitsufuji, Stefano Ermon

ICML 2022 SQ-VAE: Variational Bayes on Discrete Representation with Self-Annealed Stochastic Quantization Yuhta Takida, Takashi Shibuya, Weihsiang Liao, Chieh-Hsin Lai, Junki Ohmura, Toshimitsu Uesaka, Naoki Murata, Shusuke Takahashi, Toshiyuki Kumakura, Yuki Mitsufuji