Robust Subspace Recovery Layer for Unsupervised Anomaly Detection. - Chieh-Hsin Lai; Dongmian Zou; Gilad Lerman (ICLR, 2020)

Inverse Problems, Deep Learning, and Symmetry Breaking. - Kshitij Tayal; Chieh-Hsin Lai; Vipin Kumar 001; Ju Sun (CoRR, 2020)

Novelty Detection via Robust Variational Autoencoding. - Chieh-Hsin Lai; Dongmian Zou; Gilad Lerman (CoRR, 2020)

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)

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)

Robust Variational Autoencoding with Wasserstein Penalty for Novelty Detection. - Chieh-Hsin Lai; Dongmian Zou; Gilad Lerman (AISTATS, 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)

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)

On the Language Encoder of Contrastive Cross-modal Models. - Mengjie Zhao; Junya Ono; Zhi Zhong; Chieh-Hsin Lai; Yuhta Takida; Naoki Murata; Wei-Hsiang Liao 001; Takashi Shibuya 001; Hiromi Wakaki; Yuki Mitsufuji (ACL (Findings), 2024)

VRDMG: Vocal Restoration via Diffusion Posterior Sampling with Multiple Guidance. - Carlos Hernandez-Olivan; Koichi Saito; Naoki Murata; Chieh-Hsin Lai; Marco A. Martínez Ramírez; Wei-Hsiang Liao 001; Yuki Mitsufuji (ICASSP, 2024)

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)

GenWarp: Single Image to Novel Views with Semantic-Preserving Generative Warping. - Junyoung Seo; Kazumi Fukuda; Takashi Shibuya 001; Takuya Narihira; Naoki Murata; Shoukang Hu; Chieh-Hsin Lai; Seungryong Kim; Yuki Mitsufuji (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)

SoundCTM: Uniting Score-based and Consistency Models for Text-to-Sound Generation. - Koichi Saito; Dongjun Kim; Takashi Shibuya 001; Chieh-Hsin Lai; Zhi Zhong; Yuhta Takida; 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)

Latent Diffusion Bridges for Unsupervised Musical Audio Timbre Transfer. - Michele Mancusi; Yurii Halychanskyi; Kin Wai Cheuk; Chieh-Hsin Lai; Stefan Uhlich; Junghyun Koo; Marco A. Martínez Ramírez; Wei-Hsiang Liao 001; Giorgio Fabbro; Yuki Mitsufuji (CoRR, 2024)

A Survey on Diffusion Models for Inverse Problems. - Giannis Daras; Hyungjin Chung; Chieh-Hsin Lai; Yuki Mitsufuji; Jong Chul Ye; Peyman Milanfar; Alexandros G. Dimakis; Mauricio Delbracio (CoRR, 2024)

Bellman Diffusion: Generative Modeling as Learning a Linear Operator in the Distribution Space. - Yangming Li; Chieh-Hsin Lai; Carola-Bibiane Schönlieb; Yuki Mitsufuji; Stefano Ermon (CoRR, 2024)

Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning. - Ayano Hiranaka; Shang-Fu Chen; Chieh-Hsin Lai; Dongjun Kim; Naoki Murata; Takashi Shibuya 001; Wei-Hsiang Liao 001; Shao-Hua Sun; Yuki Mitsufuji (CoRR, 2024)

Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models. - Yong-Hyun Park; Chieh-Hsin Lai; Satoshi Hayakawa; Yuhta Takida; 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)

The Sound Demixing Challenge 2023 - Music Demixing Track. - Giorgio Fabbro; Stefan Uhlich; Chieh-Hsin Lai; Woosung Choi; Marco A. Martínez Ramírez; Wei-Hsiang Liao 001; Igor Gadelha; Geraldo Ramos; Eddie Hsu; Hugo Rodrigues; Fabian-Robert Stöter; Alexandre Défossez; et al. (Trans. Int. Soc. Music. Inf. Retr., 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)

Latent Diffusion Bridges for Unsupervised Musical Audio Timbre Transfer. - Michele Mancusi; Yurii Halychanskyi; Kin Wai Cheuk; Eloi Moliner; Chieh-Hsin Lai; Stefan Uhlich; Junghyun Koo; Marco A. Martínez Ramírez; Wei-Hsiang Liao 001; Giorgio Fabbro; Yuki Mitsufuji (ICASSP, 2025)

HERO: Human-Feedback Efficient Reinforcement Learning for Online Diffusion Model Finetuning. - Ayano Hiranaka; Shang-Fu Chen; Chieh-Hsin Lai; Dongjun Kim; Naoki Murata; Takashi Shibuya 001; Wei-Hsiang Liao 001; Shao-Hua Sun; Yuki Mitsufuji (ICLR, 2025)

Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models. - Yong-Hyun Park; Chieh-Hsin Lai; Satoshi Hayakawa; Yuhta Takida; Yuki Mitsufuji (ICLR, 2025)

SoundCTM: Unifying Score-based and Consistency Models for Full-band Text-to-Sound Generation. - Koichi Saito; Dongjun Kim; Takashi Shibuya 001; Chieh-Hsin Lai; Zhi Zhong; Yuhta Takida; 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, 2025)

Music Foundation Model as Generic Booster for Music Downstream Tasks. - Wei-Hsiang Liao 001; Yuhta Takida; Yukara Ikemiya; Zhi Zhong; Chieh-Hsin Lai; Giorgio Fabbro; Kazuki Shimada; Keisuke Toyama 002; Kin Wai Cheuk; Marco A. Martínez Ramírez; Shusuke Takahashi; Stefan Uhlich; et al. (Trans. Mach. Learn. Res., 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)

Consistency Training with Physical Constraints. - Che-Chia Chang; Chen-Yang Dai; Te-Sheng Lin; Ming-Chih Lai; Chieh-Hsin Lai (CoRR, 2025)

Training Consistency Models with Variational Noise Coupling. - Gianluigi Silvestri; Luca Ambrogioni; Chieh-Hsin Lai; Yuhta Takida; Yuki Mitsufuji (CoRR, 2025)

SteerMusic: Enhanced Musical Consistency for Zero-shot Text-Guided and Personalized Music Editing. - Xinlei Niu; Kin Wai Cheuk; Jing Zhang 052; Naoki Murata; Chieh-Hsin Lai; Michele Mancusi; Woosung Choi; Giorgio Fabbro; Wei-Hsiang Liao 001; Charles Patrick Martin; Yuki Mitsufuji (CoRR, 2025)

Concept-TRAK: Understanding how diffusion models learn concepts through concept-level attribution. - Yong-Hyun Park; Chieh-Hsin Lai; Satoshi Hayakawa; Yuhta Takida; Naoki Murata; Wei-Hsiang Liao 001; Woosung Choi; Kin Wai Cheuk; Junghyun Koo; Yuki Mitsufuji (CoRR, 2025)

Denoising Multi-Beta VAE: Representation Learning for Disentanglement and Generation. - Anshuk Uppal; Yuhta Takida; Chieh-Hsin Lai; Yuki Mitsufuji (CoRR, 2025)

Theory-Informed Improvements to Classifier-Free Guidance for Discrete Diffusion Models. - Kevin Rojas; Ye He 003; Chieh-Hsin Lai; Yuhta Takida; Yuki Mitsufuji; Molei Tao (CoRR, 2025)