Liu, Zhaoqiang

19 publications

TMLR 2025 AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael Ng, Zhenguo Li, Zhaoqiang Liu

ICML 2025 Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models Yang Zheng, Wen Li, Zhaoqiang Liu

NeurIPS 2025 Learnable Sampler Distillation for Discrete Diffusion Models Feiyang Fu, Tongxian Guo, Zhaoqiang Liu

ICML 2025 Learning Single Index Models with Diffusion Priors Anqi Tang, Youming Chen, Shuchen Xue, Zhaoqiang Liu

CVPR 2024 Accelerating Diffusion Sampling with Optimized Time Steps Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li

AAAI 2024 Efficient Algorithms for Non-Gaussian Single Index Models with Generative Priors Junren Chen, Zhaoqiang Liu

NeurIPS 2024 Generalized Eigenvalue Problems with Generative Priors Zhaoqiang Liu, Wen Li, Junren Chen

ICML 2024 The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi

NeurIPS 2023 A Unified Framework for Uniform Signal Recovery in Nonlinear Generative Compressed Sensing Junren Chen, Jonathan Scarlett, Michael Ng, Zhaoqiang Liu

ICCV 2023 DDP: Diffusion Model for Dense Visual Prediction Yuanfeng Ji, Zhe Chen, Enze Xie, Lanqing Hong, Xihui Liu, Zhaoqiang Liu, Tong Lu, Zhenguo Li, Ping Luo

ICCV 2023 DiffFit: Unlocking Transferability of Large Diffusion Models via Simple Parameter-Efficient Fine-Tuning Enze Xie, Lewei Yao, Han Shi, Zhili Liu, Daquan Zhou, Zhaoqiang Liu, Jiawei Li, Zhenguo Li

ICLR 2022 Generative Principal Component Analysis Zhaoqiang Liu, Jiulong Liu, Subhroshekhar Ghosh, Jun Han, Jonathan Scarlett

NeurIPS 2022 Misspecified Phase Retrieval with Generative Priors Zhaoqiang Liu, Xinshao Wang, Jiulong Liu

CVPR 2022 Non-Iterative Recovery from Nonlinear Observations Using Generative Models Jiulong Liu, Zhaoqiang Liu

IJCAI 2022 Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors Zhaoqiang Liu, Jun Han

NeurIPS 2021 Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors Zhaoqiang Liu, Subhroshekhar Ghosh, Jonathan Scarlett

ICML 2020 Sample Complexity Bounds for 1-Bit Compressive Sensing and Binary Stable Embeddings with Generative Priors Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett

NeurIPS 2020 The Generalized Lasso with Nonlinear Observations and Generative Priors Zhaoqiang Liu, Jonathan Scarlett

NeurIPSW 2019 Sample Complexity Lower Bounds for Compressive Sensing with Generative Models Zhaoqiang Liu, Jonathan Scarlett