Zhang, Qinsheng

18 publications

ICML 2025 Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model Is Secretly a GAN Discriminator Kaiwen Zheng, Yongxin Chen, Huayu Chen, Guande He, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang

ICLR 2025 EdgeRunner: Auto-Regressive Auto-Encoder for Artistic Mesh Generation Jiaxiang Tang, Zhaoshuo Li, Zekun Hao, Xian Liu, Gang Zeng, Ming-Yu Liu, Qinsheng Zhang

ICLR 2025 High-Quality Joint Image and Video Tokenization with Causal VAE Dawit Mureja Argaw, Xian Liu, Qinsheng Zhang, Joon Son Chung, Ming-Yu Liu, Fitsum Reda

ICLR 2025 Masked Diffusion Models Are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling Kaiwen Zheng, Yongxin Chen, Hanzi Mao, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang

CVPR 2024 Condition-Aware Neural Network for Controlled Image Generation Han Cai, Muyang Li, Qinsheng Zhang, Ming-Yu Liu, Song Han

CVPR 2024 DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Kai Li, Song Han

NeurIPS 2024 RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance Jiaojiao Fan, Haotian Xue, Qinsheng Zhang, Yongxin Chen

ICML 2024 Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue

CVPR 2023 DiffCollage: Parallel Generation of Large Content with Diffusion Models Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, Ming-Yu Liu

ICLR 2023 Fast Sampling of Diffusion Models with Exponential Integrator Qinsheng Zhang, Yongxin Chen

ICML 2023 Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, Arash Vahdat

ICLR 2023 gDDIM: Generalized Denoising Diffusion Implicit Models Qinsheng Zhang, Molei Tao, Yongxin Chen

NeurIPSW 2022 AsymQ: Asymmetric Q-Loss to Mitigate Overestimation Bias in Off-Policy Reinforcement Learning Qinsheng Zhang, Arjun Krishna, Sehoon Ha, Yongxin Chen

NeurIPSW 2022 Fast Sampling of Diffusion Models with Exponential Integrator Qinsheng Zhang, Yongxin Chen

ICLR 2022 Path Integral Sampler: A Stochastic Control Approach for Sampling Qinsheng Zhang, Yongxin Chen

ICML 2022 Variational Wasserstein Gradient Flow Jiaojiao Fan, Qinsheng Zhang, Amirhossein Taghvaei, Yongxin Chen

NeurIPS 2021 Diffusion Normalizing Flow Qinsheng Zhang, Yongxin Chen

L4DC 2020 Improving Robustness via Risk Averse Distributional Reinforcement Learning Rahul Singh, Qinsheng Zhang, Yongxin Chen