Multi-view Learning over Retinal Thickness and Visual Sensitivity on Glaucomatous Eyes. - Toshimitsu Uesaka; Kai Morino; Hiroki Sugiura; Taichi Kiwaki; Hiroshi Murata; Ryo Asaoka; Kenji Yamanishi (KDD, 2017)

Preventing Posterior Collapse Induced by Oversmoothing in Gaussian VAE. - Yuhta Takida; Wei-Hsiang Liao 001; Toshimitsu Uesaka; Shusuke Takahashi; Yuki Mitsufuji (CoRR, 2021)

SQ-VAE: Variational Bayes on Discrete Representation with Self-annealed Stochastic Quantization. - Yuhta Takida; Takashi Shibuya 001; Wei-Hsiang Liao 001; Chieh-Hsin Lai; Junki Ohmura; Toshimitsu Uesaka; Naoki Murata; Shusuke Takahashi; Toshiyuki Kumakura; Yuki Mitsufuji (ICML, 2022)

Regularizing Score-based Models with Score Fokker-Planck Equations. - Chieh-Hsin Lai; Yuhta Takida; Naoki Murata; Toshimitsu Uesaka; Yuki Mitsufuji; Stefano Ermon (CoRR, 2022)

A Versatile Diffusion-based Generative Refiner for Speech Enhancement. - Ryosuke Sawata; Naoki Murata; Yuhta Takida; Toshimitsu Uesaka; Takashi Shibuya 001; Shusuke Takahashi; Yuki Mitsufuji (CoRR, 2022)

Preventing oversmoothing in VAE via generalized variance parameterization. - Yuhta Takida; Wei-Hsiang Liao 001; Chieh-Hsin Lai; Toshimitsu Uesaka; Shusuke Takahashi; Yuki Mitsufuji (Neurocomputing, 2022)

Diffroll: Diffusion-Based Generative Music Transcription with Unsupervised Pretraining Capability. - Kin Wai Cheuk; Ryosuke Sawata; Toshimitsu Uesaka; Naoki Murata; Naoya Takahashi; Shusuke Takahashi; Dorien Herremans; Yuki Mitsufuji (ICASSP, 2023)

Unsupervised Vocal Dereverberation with Diffusion-Based Generative Models. - Koichi Saito; Naoki Murata; Toshimitsu Uesaka; Chieh-Hsin Lai; Yuhta Takida; Takao Fukui; Yuki Mitsufuji (ICASSP, 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 (ICML, 2023)

Diffiner: A Versatile Diffusion-based Generative Refiner for Speech Enhancement. - Ryosuke Sawata; Naoki Murata; Yuhta Takida; Toshimitsu Uesaka; Takashi Shibuya 001; Shusuke Takahashi; Yuki Mitsufuji (INTERSPEECH, 2023)

Adversarially Slicing Generative Networks: Discriminator Slices Feature for One-Dimensional Optimal Transport. - Yuhta Takida; Masaaki Imaizumi; Chieh-Hsin Lai; Toshimitsu Uesaka; Naoki Murata; Yuki Mitsufuji (CoRR, 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 (CoRR, 2023)

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer. - Yuhta Takida; Masaaki Imaizumi; Takashi Shibuya 001; Chieh-Hsin Lai; Toshimitsu Uesaka; Naoki Murata; Yuki Mitsufuji (Zenodo, 2023)

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer. - Yuhta Takida; Masaaki Imaizumi; Takashi Shibuya 001; Chieh-Hsin Lai; Toshimitsu Uesaka; Naoki Murata; Yuki Mitsufuji (Zenodo, 2023)

Manifold Preserving Guided Diffusion. - Yutong He; Naoki Murata; Chieh-Hsin Lai; Yuhta Takida; Toshimitsu Uesaka; Dongjun Kim; Wei-Hsiang Liao 001; Yuki Mitsufuji; J. Zico Kolter; Ruslan Salakhutdinov; Stefano Ermon (ICLR, 2024)

Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion. - Dongjun Kim; Chieh-Hsin Lai; Wei-Hsiang Liao 001; Naoki Murata; Yuhta Takida; Toshimitsu Uesaka; Yutong He; Yuki Mitsufuji; Stefano Ermon (ICLR, 2024)

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer. - Yuhta Takida; Masaaki Imaizumi; Takashi Shibuya 001; Chieh-Hsin Lai; Toshimitsu Uesaka; Naoki Murata; Yuki Mitsufuji (ICLR, 2024)

PaGoDA: Progressive Growing of a One-Step Generator from a Low-Resolution Diffusion Teacher. - Dongjun Kim; Chieh-Hsin Lai; Wei-Hsiang Liao 001; Yuhta Takida; Naoki Murata; Toshimitsu Uesaka; Yuki Mitsufuji; Stefano Ermon (NeurIPS, 2024)

Understanding Multimodal Contrastive Learning Through Pointwise Mutual Information. - Toshimitsu Uesaka; Taiji Suzuki; Yuhta Takida; Chieh-Hsin Lai; Naoki Murata; Yuki Mitsufuji (CoRR, 2024)

DisMix: Disentangling Mixtures of Musical Instruments for Source-level Pitch and Timbre Manipulation. - Yin-Jyun Luo; Kin Wai Cheuk; Woosung Choi; Toshimitsu Uesaka; Keisuke Toyama 002; Koichi Saito; Chieh-Hsin Lai; Yuhta Takida; Wei-Hsiang Liao 001; Simon Dixon; Yuki Mitsufuji (CoRR, 2024)

G2D2: Gradient-guided Discrete Diffusion for image inverse problem solving. - Naoki Murata; Chieh-Hsin Lai; Yuhta Takida; Toshimitsu Uesaka; Bac Nguyen; Stefano Ermon; Yuki Mitsufuji (CoRR, 2024)

Mitigating Embedding Collapse in Diffusion Models for Categorical Data. - Bac Nguyen; Chieh-Hsin Lai; Yuhta Takida; Naoki Murata; Toshimitsu Uesaka; Stefano Ermon; Yuki Mitsufuji (CoRR, 2024)

HQ-VAE: Hierarchical Discrete Representation Learning with Variational Bayes. - Yuhta Takida; Yukara Ikemiya; Takashi Shibuya 001; Kazuki Shimada; Woosung Choi; Chieh-Hsin Lai; Naoki Murata; Toshimitsu Uesaka; Kengo Uchida; Wei-Hsiang Liao 001; Yuki Mitsufuji (Trans. Mach. Learn. Res., 2024)

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer. - Yuhta Takida; Masaaki Imaizumi; Takashi Shibuya 001; Chieh-Hsin Lai; Toshimitsu Uesaka; Naoki Murata; Yuki Mitsufuji (Zenodo, 2024)

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, 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 (Trans. Mach. Learn. Res., 2025)