Hyperdimensional fingerprints use algebraic vector operations to create training-free molecular representations that outperform conventional fingerprints on similarity preservation and property prediction at low dimensions.
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2 Pith papers cite this work, alongside 575 external citations. Polarity classification is still indexing.
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Pith papers citing it
575
external citations · OpenAlex
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
GLACIER combines graph, SMILES, and descriptor encoders with Finsler fusion and contrastive distillation to produce an efficient multimodal model for molecular property prediction.
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Hyper-Dimensional Fingerprints as Molecular Representations
Hyperdimensional fingerprints use algebraic vector operations to create training-free molecular representations that outperform conventional fingerprints on similarity preservation and property prediction at low dimensions.
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GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction
GLACIER combines graph, SMILES, and descriptor encoders with Finsler fusion and contrastive distillation to produce an efficient multimodal model for molecular property prediction.