Hyperdimensional fingerprints use algebraic operations on high-dimensional vectors to create training-free molecular representations that preserve similarity better than Morgan fingerprints at low dimensions and improve downstream tasks like property prediction and Bayesian optimization.
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Hyper-Dimensional Fingerprints as Molecular Representations
Hyperdimensional fingerprints use algebraic operations on high-dimensional vectors to create training-free molecular representations that preserve similarity better than Morgan fingerprints at low dimensions and improve downstream tasks like property prediction and Bayesian optimization.