Cheng Lu

According to our database, Cheng Lu authored at least 16 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Towards Efficient and Exact Optimization of Language Model Alignment.

Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, Minlie Huang

CoRR, 2024

Towards Efficient Exact Optimization of Language Model Alignment.

Haozhe Ji, Cheng Lu, Yilin Niu, Pei Ke, Hongning Wang, Jun Zhu, Jie Tang, Minlie Huang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing.

Shen Nie, Hanzhong Allan Guo, Cheng Lu, Yuhao Zhou, Chenyu Zheng, Chongxuan Li

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Score Regularized Policy Optimization through Diffusion Behavior.

Huayu Chen, Cheng Lu, Zhengyi Wang, Hang Su, Jun Zhu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics.

Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation.

Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

On Calibrating Diffusion Probabilistic Models.

Tianyu Pang, Cheng Lu, Chao Du, Min Lin, Shuicheng Yan, Zhijie Deng

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Gaussian Mixture Solvers for Diffusion Models.

Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Improved Techniques for Maximum Likelihood Estimation for Diffusion ODEs.

Kaiwen Zheng, Cheng Lu, Jianfei Chen, Jun Zhu

Proceedings of the International Conference on Machine Learning, 2023

Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning.

Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu

Proceedings of the International Conference on Machine Learning, 2023

Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling.

Huayu Chen, Cheng Lu, Chengyang Ying, Hang Su, Jun Zhu

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.

Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

CoRR, 2022

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps.

Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching.

Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu

Proceedings of the International Conference on Machine Learning, 2022

2021

Implicit Normalizing Flows.

Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

VFlow: More Expressive Generative Flows with Variational Data Augmentation.

Jianfei Chen, Cheng Lu, Biqi Chenli, Jun Zhu, Tian Tian

Proceedings of the 37th International Conference on Machine Learning, 2020