- [1] Wenhao Sun , Ji Li , and Zhaoqiang Liu* , Just-in-time: Training-free spatial acceleration for diffusion Transformers, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Feb 2026.
- [2] Yang Zheng, , Jiahua Liu , Tongyao Pang , Wen Li , and Zhaoqiang Liu* , Outlier-robust diffusion solvers for inverse problem, to IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Feb 2026.
- [3] Youming Chen and Zhaoqiang Liu* , Diffusion model based signal recovery under 1-bit quantization, AAAI Conference on Artificial Intelligence (AAAI), Jan 2026.
- [4] Feiyang Fu , Tongxian Guo , and Zhaoqiang Liu* , Learnable sampler distillation for discrete diffusion models, Conference on Neural Information Processing Systems (NeurIPS spotlight presentation), Dec 2025.
- [5] Yang Zheng , Wen Li , and Zhaoqiang Liu* , Integrating intermediate layer optimization and projected gradient descent for solving inverse problems with diffusion models, International Conference on Machine Learning (ICML), Jul 2025.
- [6] Anqi Tang , Youming Chen , Shuchen Xue , and Zhaoqiang Liu* , Learning single index models with diffusion priors, International Conference on Machine Learning (ICML), Jul 2025.
- [7] Yihang Gao , Chuanyang Zheng , Enze Xie , Han Shi , Tianyang Hu , Yu Li , Michael K. Ng , Zhenguo Li , and Zhaoqiang Liu* , AlgoFormer: An efficient Transformer framework with algorithmic structures, Transactions on Machine Learning Research, Jan 2025.
- [8] Junren Chen , Michael K. Ng , and Zhaoqiang Liu , Solving quadratic systems with full-rank matrices using sparse or generative priors, IEEE Transactions on Signal Processing, Jan 2025.
- [9] Zhaoqiang Liu , Wen Li , and Junren Chen , Generalized eigenvalue problems with generative priors, Conference on Neural Information Processing Systems (NeurIPS), Dec 2024.
- [10] Junren Chen , Zhaoqiang Liu , Meng Ding , and Michael K. Ng , Uniform recovery guarantees for quantized corrupted sensing with structured or generative priors, SIAM Journal on Imaging Sciences, Sep 2024.
- [11] Jiajun Ma , Shuchen Xue , Tianyang Hu , Wenjia Wang , Zhaoqiang Liu , Zhenguo Li , Zhi-Ming Ma , and Kenji Kawaguchi , The surprising effectiveness of skip-tuning in diffusion sampling, International Conference on Machine Learning (ICML), Jul 2024.
- [12] Shuchen Xue , Zhaoqiang Liu* , Fei Chen , Shifeng Zhang , Tianyang Hu , Enze Xie , and Zhenguo Li , Accelerating diffusion sampling with optimized time steps, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2024.
- [13] Junren Chen and Zhaoqiang Liu* , Efficient algorithms for non-Gaussian single index models with generative priors, AAAI Conference on Artificial Intelligence (AAAI), Jan 2024.
- [14] Junren Chen* , Jonathan Scarlett , Michael K. Ng , and Zhaoqiang Liu* , A unified framework for uniform signal recovery in nonlinear generative compressed sensing, Conference on Neural Information Processing Systems (NeurIPS), Dec 2023.
- [15] Enze Xie , Lewei Yao , Han Shi , Zhili Liu , Daquan Zhou , Zhaoqiang Liu , Jiawei Li , and Zhenguo Li , DiffFit: Unlocking transferability of large diffusion models via simple parameter-efficient fine-tuning, International Conference on Computer Vision (ICCV oral presentation), Jun 2023.
- [16] Yuanfeng Ji , Zhe Chen , Enze Xie , Lanqing Hong , Xihui Liu , Zhaoqiang Liu , Tong Lu , Zhenguo Li , and Ping Luo , DDP: Diffusion model for dense visual prediction, International Conference on Computer Vision (ICCV), Jun 2023.
- [17] Zhaoqiang Liu , Xinshao Wang , and Jiulong Liu , Misspecified phase retrieval with generative priors, Conference on Neural Information Processing Systems (NeurIPS), Dec 2022.
- [18] Jiulong Liu and Zhaoqiang Liu* , Non-iterative recovery from nonlinear observations using generative models, IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Jun 2022.
- [19] Zhaoqiang Liu , Jiulong Liu , Subhroshekhar Ghosh , Jun Han , and Jonathan Scarlett , Generative principal component analysis, International Conference on Learning Representations (ICLR), Apr 2022.
- [20] Zhaoqiang Liu , Subhroshekhar Ghosh , and Jonathan Scarlett , Towards sample-optimal compressive phase retrieval with sparse and generative priors, Conference on Neural Information Processing Systems (NeurIPS), Dec 2021.
刘昭强 (教授)
教授 博士生导师
主要任职：教授
性别：男
学历：博士研究生毕业
学位：哲学博士学位
入职时间：2024-01-09
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