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 Coakley et alK. L. Coakley, T. Snelleman, H. Hoos, and O. E. Gundersen, "The embrace of open science: An analysis of a decade of AI research and 56 800 conference papers," Under Review, 2026..
Predicting Molecular Conformation via Dynamic Graph Score Matching
Authors: Shitong Luo, Chence Shi, Minkai Xu, Jian Tang
NeurIPS 2021 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments across multiple tasks show that the DGSM outperforms state-of-the-art baselines by a large margin, and it is capable of generating conformations for a broader range of systems such as proteins and multi-molecular complexes. |
| Researcher Affiliation | Academia | Shitong Luo*1, Chence Shi*2,3, Minkai Xu2,3, Jian Tang2,4,5 1Peking University 2Mila Québec AI Institute 3Université de Montréal 4HEC Montréal 5CIFAR AI Research Chair EMAIL , EMAIL EMAIL , EMAIL |
| Pseudocode | Yes | Algorithm 1 Annealed Langevin dynamics |
| Open Source Code | No | The paper does not include an unambiguous statement or link indicating that the source code for the described methodology is publicly available. |
| Open Datasets | Yes | Following previous works [34, 43], we use the GEOM-QM9 and GEOM-Drugs [1] datasets for this task. |
| Dataset Splits | No | The paper mentions 'train-test split' but does not explicitly state the use of a distinct 'validation' dataset split for hyperparameter tuning or early stopping. |
| Hardware Specification | No | The paper does not provide specific details about the hardware (e.g., GPU/CPU models, memory) used for running the experiments. |
| Software Dependencies | No | The paper does not provide specific version numbers for software dependencies or libraries used in the experiments. |
| Experiment Setup | Yes | The threshold δ of COV score is 0.5Å for GEOM-QM9 and 1.25Å for GEOM-Drugs following Xu et al. [43]. We here take the prior distribution as a standard Gaussian N(R0 | 0, I). Then, we update the conformation by running T steps of Langevin dynamic to get a sample from each noise conditional score network sθ(R, σi) sequentially with a special step size schedule αi = ε σ2 i /σ2 L. |