Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better

1 code implementation • 2 Apr 2024 • Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

For example, LCSC achieves better performance using 1 number of function evaluation (NFE) than the base model with 2 NFE on consistency distillation, and decreases the NFE of DM from 15 to 9 while maintaining the generation quality on CIFAR-10.

A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models

no code implementations • 12 Dec 2023 • Enshu Liu, Xuefei Ning, Huazhong Yang, Yu Wang

In this paper, we propose a unified sampling framework (USF) to study the optional strategies for solver.

OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models

1 code implementation • 15 Jun 2023 • Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang

Diffusion probabilistic models (DPMs) are a new class of generative models that have achieved state-of-the-art generation quality in various domains.

Dynamic Ensemble of Low-fidelity Experts: Mitigating NAS "Cold-Start"

1 code implementation • 2 Feb 2023 • Junbo Zhao, Xuefei Ning, Enshu Liu, Binxin Ru, Zixuan Zhou, Tianchen Zhao, Chen Chen, Jiajin Zhang, Qingmin Liao, Yu Wang

In the first step, we train different sub-predictors on different types of available low-fidelity information to extract beneficial knowledge as low-fidelity experts.

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