VecMol: Vector-Field Representations for 3D Molecule Generation
Generative modeling of three-dimensional (3D) molecules is a fundamental yet challenging problem in drug discovery and materials science. Existing approaches typically represent molecules as 3D graphs and co-generate discrete atom types with continuous atomic coordinates, leading to intrinsic learning difficulties such as heterogeneous modality entanglement and geometry-chemistry coherence constraints. We propose VecMol, a paradigm-shifting framework that reimagines molecular representation by modeling 3D molecules as continuous vector fields over Euclidean space, where vectors point toward nearby atoms and implicitly encode molecular structure. The vector field is parameterized by a neur...
| Authors | Yuchen Hua, Xingang Peng, Jianzhu Ma et al. |
|---|---|
| Primary category | stat.ML |
| Published | 13 March 2026 |
| Last updated at source | 13 March 2026 |
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