Cheng Lu

Affiliations:
  • Tsinghua University, China


According to our database1, Cheng Lu authored at least 13 papers between 2020 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2023
The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing.
CoRR, 2023

Gaussian Mixture Solvers for Diffusion Models.
CoRR, 2023

DPM-Solver-v3: Improved Diffusion ODE Solver with Empirical Model Statistics.
CoRR, 2023

Score Regularized Policy Optimization through Diffusion Behavior.
CoRR, 2023

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation.
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.
Proceedings of the International Conference on Machine Learning, 2023

Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning.
Proceedings of the International Conference on Machine Learning, 2023

Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models.
CoRR, 2022

DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps.
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.
Proceedings of the International Conference on Machine Learning, 2022

2021
Implicit Normalizing Flows.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
VFlow: More Expressive Generative Flows with Variational Data Augmentation.
Proceedings of the 37th International Conference on Machine Learning, 2020


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