Rem3Di builds fixed-length, chirality-aware molecular descriptors by aggregating frozen atomistic foundation-model features with attention and a self-supervised denoising pretraining objective, matching or beating graph/2D baselines on drug-property benchmarks.
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Rem3Di: Learning smooth, chiral 3D molecular descriptors from atomistic foundation models
Rem3Di builds fixed-length, chirality-aware molecular descriptors by aggregating frozen atomistic foundation-model features with attention and a self-supervised denoising pretraining objective, matching or beating graph/2D baselines on drug-property benchmarks.