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; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1]
CryoFM: A Flow-based Foundation Model for Cryo-EM Densities
Authors: Yi Zhou, Yilai Li, Jing Yuan, Quanquan Gu
ICLR 2025 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | 5 EXPERIMENTS |
| Researcher Affiliation | Industry | Yi Zhou , Yilai Li , Jing Yuan , Quanquan Gu Byte Dance Research EMAIL |
| Pseudocode | Yes | Algorithm 1 Flow Posterior Sampling |
| Open Source Code | No | No explicit statement about releasing the code for the methodology described in this paper is provided. The paper mentions using publicly available code from Stable Diffusion and Hugging Face's diffusers for related components, but not their own implementation of CRYOFM. |
| Open Datasets | Yes | Our training dataset consists of deposited sharpened density maps from the EMDB (ww PDB Consortium, 2023)... The EMDB IDs of the training and testing data used in this paper have been uploaded to https://figshare.com/s/9ef2614108391c04d910. |
| Dataset Splits | Yes | This curation resulted in a total of 3479 density maps, where 32 density maps were selected as test set and excluded from training. |
| Hardware Specification | Yes | Training Hardware 8 A100 |
| Software Dependencies | No | The paper mentions the use of 'Fairseq Adam (Ott et al., 2019) optimizer' but does not provide a specific version number for the Fairseq library itself or any other key software dependencies with their versions. |
| Experiment Setup | Yes | In all experiments, we employed the Fairseq Adam (Ott et al., 2019) optimizer with a default learning rate of 1e-4, betas set to (0.9, 0.98), and a weight decay of 0.01. A linear warm-up strategy was applied during the first 2000 steps of training. |