Fast Sampling of Diffusion Models with Exponential Integrator
Authors: Qinsheng Zhang, Yongxin Chen
ICLR 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We conduct comprehensive experiments to validate the efficacy of DEIS. For instance, with a pre-trained model (Song et al., 2020b), DEIS is able to reach 4.17 FID with 10 NFEs, and 2.86 FID with 20 NFEs on CIFAR10. |
| Researcher Affiliation | Academia | Qinsheng Zhang Georgia Institute of Technology qzhang419@gatech.edu Yongxin Chen Georgia Institute of Technology yongchen@gatech.edu |
| Pseudocode | Yes | Algorithm 1 t AB-DEIS |
| Open Source Code | Yes | Project page and code: https://qsh-zh.github.io/deis. |
| Open Datasets | Yes | For instance, with a pre-trained model (Song et al., 2020b), DEIS is able to reach 4.17 FID with 10 NFEs, and 2.86 FID with 20 NFEs on CIFAR10. (Abstract), 64 64 Celeb A (Liu et al., 2015) with pre-trained model from Song et al. (2020a), class-conditioned 64 64 Image Net (Deng et al., 2009) with pre-trained model (Dhariwal & Nichol, 2021) |
| Dataset Splits | No | No specific dataset split information (percentages, sample counts, or explicit methodology) was found. |
| Hardware Specification | No | No specific hardware details (e.g., GPU/CPU models, memory) were provided for the experimental setup. |
| Software Dependencies | No | We implemented our approach in Jax and Py Torch. |
| Experiment Setup | Yes | Due to numerical issues, we set ending time t0 in DMs during sampling a non-zero number. Song et al. (2020b) suggests t0 = 10-3 for VPSDE and t0 = 10-5 for VESDE. One such option is the quadratic timestep suggested in (Song et al., 2020a) |