@article{wang2024onedp,title={One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation},author={Wang, Zhendong and Li, Zhaoshuo and Mandlekar, Ajay and Xu, Zhenjia and Fan, Jiaojiao and Narang, Yashraj and Fan, Linxi and et al},journal={ArXiv Preprint},year={2024},url={https://arxiv.org/abs/2410.21257},}
Preprint
Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step
Mingyuan Zhou, Huangjie Zheng, Yi Gu, and 2 more authors
@article{zhou2024sida,title={Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step},author={Zhou, Mingyuan and Zheng, Huangjie and Gu, Yi and Wang, Zhendong and Huang, Hai},journal={ArXiv Preprint},year={2024},url={https://arxiv.org/abs/2410.14919},}
Preprint
Long and Short Guidance in Score identity Distillation for One-Step Text-to-Image Generation
Mingyuan Zhou, Zhendong Wang, Huangjie Zheng, and 1 more author
@article{zhou2024sidlsg,title={Long and Short Guidance in Score identity Distillation for One-Step Text-to-Image Generation},author={Zhou, Mingyuan and Wang, Zhendong and Zheng, Huangjie and Huang, Hai},journal={ArXiv Preprint},year={2024},url={https://arxiv.org/abs/2406.01561},}
ICML 2024
Score identity distillation: Exponentially fast distillation of pretrained diffusion models for one-step generation
Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, and 1 more author
International Conference on Machine Learning 2024, 2024
@article{zhou2024sid,title={Score identity distillation: Exponentially fast distillation of pretrained diffusion models for one-step generation},author={Zhou, Mingyuan and Zheng, Huangjie and Wang, Zhendong and Huang, Hai},journal={International Conference on Machine Learning 2024},year={2024},url={https://arxiv.org/abs/2404.04057},}
Preprint
Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment
Yueqin Yin, Zhendong Wang, Yujia Xie, and 2 more authors
@article{yin2024sapo,title={Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment},author={Yin, Yueqin and Wang, Zhendong and Xie, Yujia and Chen, Weizhu and Zhou, Mingyuan},journal={ArXiv Preprint},year={2024},url={https://arxiv.org/abs/2405.20830},}
NeurIPS 2023
Diffusion Policies creating a Trust Region for Offline Reinforcement Learning
Tianyu Chen, Zhendong Wang, and Mingyuan Zhou
Advances in Neural Information Processing Systems 2024, 2024
@article{chen2024tdql,title={Diffusion Policies creating a Trust Region for Offline Reinforcement Learning},author={Chen, Tianyu and Wang, Zhendong and Zhou, Mingyuan},journal={Advances in Neural Information Processing Systems 2024},year={2024},url={https://arxiv.org/abs/2405.19690},}
Preprint
Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization
Yi Gu, Zhendong Wang, Yueqin Yin, and 2 more authors
@article{yi2024diffusionrpo,title={Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization},author={Gu, Yi and Wang, Zhendong and Yin, Yueqin and Xie, Yujia and Zhou, Mingyuan},journal={ArXiv Preprint},year={2024},url={https://arxiv.org/abs/2406.06382},}
Preprint
Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts
Yueqin Yin, Zhendong Wang, Yi Gu, and 3 more authors
@article{yin2024relative,title={Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts},author={Yin, Yueqin and Wang, Zhendong and Gu, Yi and Huang, Hai and Chen, Weizhu and Zhou, Mingyuan},journal={ArXiv Preprint:2402.10958},year={2024},url={https://arxiv.org/abs/2402.10958},}
2023
Preprint
Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts
Tianqi Chen, Yongfei Liu, Zhendong Wang, and 4 more authors
@article{chen2023improving,title={Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts},author={Chen, Tianqi and Liu, Yongfei and Wang, Zhendong and Yuan, Jianbo and You, Quanzeng and Yang, Hongxia and Zhou, Mingyuan},journal={ArXiv Preprint:2312.01408},year={2023},url={https://arxiv.org/abs/2312.01408},}
ICLR 2024
Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling
Huangjie Zheng, Zhendong Wang, Jianbo Yuan, and 5 more authors
The Twelfth International Conference on Learning Representations, 2023
@article{zheng2023learning,title={Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling},author={Zheng, Huangjie and Wang, Zhendong and Yuan, Jianbo and Ning, Guanghan and He, Pengcheng and You, Quanzeng and Yang, Hongxia and Zhou, Mingyuan},journal={The Twelfth International Conference on Learning Representations},year={2023},url={https://arxiv.org/abs/2310.06389},}
NeurIPS 2023
Beta Diffusion
Mingyuan Zhou, Tianqi Chen, Zhendong Wang, and 1 more author
Advances in Neural Information Processing Systems, 2023
@article{zhou2023betadiffusion,title={Beta Diffusion},author={Zhou, Mingyuan and Chen, Tianqi and Wang, Zhendong and Zheng, Huangjie},journal={Advances in Neural Information Processing Systems},year={2023},url={https://arxiv.org/pdf/2309.07867},}
NeurIPS 2023
In-Context Learning Unlocked for Diffusion Models
Zhendong Wang, Yifan Jiang, Yadong Lu, and 5 more authors
Advances in Neural Information Processing Systems, 2023
@article{wang2023context,title={In-Context Learning Unlocked for Diffusion Models},author={Wang, Zhendong and Jiang, Yifan and Lu, Yadong and Shen, Yelong and He, Pengcheng and Chen, Weizhu and Wang, Zhangyang and Zhou, Mingyuan},journal={Advances in Neural Information Processing Systems},year={2023},url={https://arxiv.org/abs/2305.01115},}
NeurIPS 2023
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
Zhendong Wang, Yifan Jiang, Huangjie Zheng, and 5 more authors
Advances in Neural Information Processing Systems, 2023
@article{wang2023patch,title={Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models},author={Wang, Zhendong and Jiang, Yifan and Zheng, Huangjie and Wang, Peihao and He, Pengcheng and Wang, Zhangyang and Chen, Weizhu and Zhou, Mingyuan},journal={Advances in Neural Information Processing Systems},year={2023},url={https://arxiv.org/abs/2304.12526},}
ICLR 2023
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
Zhendong Wang, J Jonathan Hunt, and Mingyuan Zhou
International Conference on Learning Representations, 2023
@article{wang2023diffusioninrl,title={Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning},author={Wang, Zhendong and Hunt, J Jonathan and Zhou, Mingyuan},journal={International Conference on Learning Representations},year={2023},url={https://arxiv.org/abs/2208.06193},}
ICLR 2023
Diffusion-GAN: Training GANs with Diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He, and 2 more authors
International Conference on Learning Representations, 2023
@article{wang2023diffusiongan,title={Diffusion-GAN: Training GANs with Diffusion},author={Wang, Zhendong and Zheng, Huangjie and He, Pengcheng and Chen, Weizhu and Zhou, Mingyuan},journal={International Conference on Learning Representations},year={2023},url={https://arxiv.org/abs/2206.02262},}
AISTATS 2023
Probabilistic Conformal Prediction Using Conditional Random Samples
Zhendong* Wang, Ruijiang* Gao, Mingzhang* Yin, and 2 more authors
International Conference on Artificial Intelligence and Statistics 2023, 2023
@article{wang2023pcp,title={Probabilistic Conformal Prediction Using Conditional Random Samples},author={Wang, Zhendong and Gao, Ruijiang and Yin, Mingzhang and Zhou, Mingyuan and Blei, David M},journal={International Conference on Artificial Intelligence and Statistics 2023},year={2023},url={https://arxiv.org/abs/2206.06584},}
2022
Preprint
A Regularized Implicit Policy for Offline Reinforcement Learning
Shentao* Yang, Zhendong* Wang, Huangjie Zheng, and 2 more authors
@article{yang2022implicitpi,title={A Regularized Implicit Policy for Offline Reinforcement Learning},author={Yang, Shentao and Wang, Zhendong and Zheng, Huangjie and Feng, Yihao and Zhou, Mingyuan},journal={ArXiv Preprint:2202.09673},year={2022},url={https://arxiv.org/abs/2202.09673},}
2020
ICML 2020
Thompson sampling via local uncertainty
Zhendong Wang, and Mingyuan Zhou
In International Conference on Machine Learning, 2020
@inproceedings{wang2020thompson,title={Thompson sampling via local uncertainty},author={Wang, Zhendong and Zhou, Mingyuan},booktitle={International Conference on Machine Learning},pages={10115--10125},year={2020},organization={PMLR},}
NeurIPS 2020
Implicit distributional reinforcement learning
Yuguang* Yue, Zhendong* Wang, and Mingyuan Zhou
Advances in Neural Information Processing Systems, 2020
@article{yue2020implicit,title={Implicit distributional reinforcement learning},author={Yue, Yuguang and Wang, Zhendong and Zhou, Mingyuan},journal={Advances in Neural Information Processing Systems},volume={33},pages={7135--7147},year={2020},}
ICLR 2020
Adaptive correlated Monte Carlo for contextual categorical sequence generation
Xinjie Fan, Yizhe Zhang, Zhendong Wang, and 1 more author
International Conference on Learning Representations, 2020
@article{fan2020adaptive,title={Adaptive correlated Monte Carlo for contextual categorical sequence generation},author={Fan, Xinjie and Zhang, Yizhe and Wang, Zhendong and Zhou, Mingyuan},journal={International Conference on Learning Representations},year={2020},}