Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Optimal Transport-Guided Conditional Score-Based Diffusion Model
Authors: Xiang Gu, Liwei Yang, Jian Sun, Zongben Xu
NeurIPS 2023 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Extensive experiments on unpaired super-resolution and semi-paired image-to-image translation demonstrated the effectiveness of the proposed OTCS model. |
| Researcher Affiliation | Academia | 1 School of Mathematics and Statistics, Xi an Jiaotong University, Xi an, China 2 Pazhou Laboratory (Huangpu), Guangzhou, China 3 Peng Cheng Laboratory, Shenzhen, China EMAIL EMAIL |
| Pseudocode | Yes | The pseudo-code for training uĻ, vĻ is given in Appendix A. ... The pseudo-code of the training algorithm is given in Appendix A. |
| Open Source Code | Yes | Code is available at https://github.com/XJTU-XGU/OTCS. |
| Open Datasets | Yes | We conduct extensive experiments on unpaired super-resolution and semi-paired I2I tasks... Celeb A dataset [41]. ... images of cat, fox, and leopard from AFHQ [48] dataset... translation from MNIST [49] to Chinese-MNIST [50]. |
| Dataset Splits | No | The paper mentions splitting the dataset into A1, B1, C1 and training on A0, B1, and testing on C0, but it does not explicitly mention a 'validation' split or set. |
| Hardware Specification | No | The paper does not provide specific hardware details such as GPU or CPU models used for running experiments. |
| Software Dependencies | No | The paper does not provide specific software dependencies with version numbers (e.g., Python 3.x, PyTorch 1.x) that were used for the implementation. |
| Experiment Setup | Yes | M = 0.2 in experiments. ... where Ļ is set to 0.1. |