GEOM-QM-9

The 'GEOM-QM-9' dataset is a benchmark that contains molecular graphs and their corresponding low-energy conformations, used to evaluate the performance of methods in generating conformer ensembles and identifying ground-state structures.

Papers using GEOM-QM-9 (8)

Sampling 3D Molecular Conformers with Diffusion Transformers2025 · 1 citesEnergy-Guided Flow Matching Enables Few-Step Conformer Generation and Ground-State Identification2025Flow-Matching Based Refiner for Molecular Conformer Generation2025Rao-Blackwell Gradient Estimators for Equivariant Denoising Diffusion2025Do Deep Learning Methods Really Perform Better in Molecular Conformation Generation?2023 · 6 citesEC-Conf: An Ultra-fast Diffusion Model for Molecular Conformation Generation with Equivariant Consistency2023Weisfeiler Leman for Euclidean Equivariant Machine Learning2024Mitigating Exposure Bias in Score-Based Generation of Molecular Conformations2024