Packora: Systematic Design for Generative Molecular Crystal Structure Prediction
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TL;DR - Packora is a flow-based generative model that jointly predicts molecular crystal atomic coordinates and lattices from molecular graphs. It improves structure generation and ranking across six benchmarks while supporting complex crystal types and flexible conditioning.
- Handles multi-component and organometallic crystals within one model.
- Conditions on any subset of conformers, stereochemical labels, and space-group information.
- Separately evaluates generation quality and end-to-end ranking under a shared relaxation and ranking pipeline.
- Achieves the best matched-budget coverage across all six generation benchmarks, with better experimental-form recovery, lower ranks, and faster ranking convergence than baselines.
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Packora: Systematic Design for Generative Molecular Crystal Structure Prediction
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Hugging Face upvotes 0
TL;DR - Packora is a flow-based generative model that jointly predicts molecular crystal atomic coordinates and lattices from molecular graphs. It improves structure generation and ranking across six benchmarks while supporting complex crystal types and flexible conditioning.
- Handles multi-component and organometallic crystals within one model.
- Conditions on any subset of conformers, stereochemical labels, and space-group information.
- Separately evaluates generation quality and end-to-end ranking under a shared relaxation and ranking pipeline.
- Achieves the best matched-budget coverage across all six generation benchmarks, with better experimental-form recovery, lower ranks, and faster ranking convergence than baselines.