| 2026 | AAAI | Diffusion Model Based Signal Recovery Under 1-Bit Quantization. | Youming Chen, Zhaoqiang Liu |
| 2025 | ICML | Learning Single Index Models with Diffusion Priors. | Anqi Tang, Youming Chen, Shuchen Xue, Zhaoqiang Liu |
| 2025 | ICML | Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models. | Yang Zheng, Wen Li, Zhaoqiang Liu |
| 2024 | AAAI | Efficient Algorithms for Non-gaussian Single Index Models with Generative Priors. | Junren Chen, Zhaoqiang Liu |
| 2024 | CVPR | Accelerating Diffusion Sampling with Optimized Time Steps. | Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li |
| 2024 | ICML | 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 |
| 2023 | ICCV | 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 |
| 2023 | ICCV | 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 |
| 2022 | CVPR | Non-Iterative Recovery from Nonlinear Observations using Generative Models. | Jiulong Liu, Zhaoqiang Liu |
| 2022 | ICLR | Generative Principal Component Analysis. | Zhaoqiang Liu, Jiulong Liu, Subhroshekhar Ghosh, Jun Han, Jonathan Scarlett |
| 2022 | IJCAI | Projected Gradient Descent Algorithms for Solving Nonlinear Inverse Problems with Generative Priors. | Zhaoqiang Liu, Jun Han |
| 2021 | ITW | Robust 1-bit Compressive Sensing with Partial Gaussian Circulant Matrices and Generative Priors. | Zhaoqiang Liu, Subhroshekhar Ghosh, Jonathan Scarlett |
| 2020 | ICML | Sample Complexity Bounds for 1-bit Compressive Sensing and Binary Stable Embeddings with Generative Priors. | Zhaoqiang Liu, Selwyn Gomes, Avtansh Tiwari, Jonathan Scarlett |
| 2019 | ICASSP | Model Selection for Nonnegative Matrix Factorization by Support Union Recovery. | Zhaoqiang Liu |
| 2019 | ICASSP | Error Bounds for Spectral Clustering over Samples from Spherical Gaussian Mixture Models. | Zhaoqiang Liu |
| 2018 | ISIT | The Informativeness of k-Means for Learning Mixture Models. | Zhaoqiang Liu, Vincent Y. F. Tan |
| 2018 | ITA | Rank-One NMF-Based Initialization for NMF and Relative Error Bounds Under a Geometric Assumption. | Zhaoqiang Liu, Vincent Y. F. Tan |
| 2017 | ICASSP | Relative error bounds for nonnegative matrix factorization under a geometric assumption. | Zhaoqiang Liu, Vincent Y. F. Tan |