A ModernBERT-based encoder trained with masked language modeling on SMILES-annotated scientific documents plus a contrastive stage yields embeddings that are competitive on both molecular property prediction and scientific NLP tasks.
Variational Gaussian Processes: A Functional Analysis View
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abstract
Variational Gaussian process (GP) approximations have become a standard tool in fast GP inference. This technique requires a user to select variational features to increase efficiency. So far the common choices in the literature are disparate and lacking generality. We propose to view the GP as lying in a Banach space which then facilitates a unified perspective. This is used to understand the relationship between existing features and to draw a connection between kernel ridge regression and variational GP approximations.
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Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language
A ModernBERT-based encoder trained with masked language modeling on SMILES-annotated scientific documents plus a contrastive stage yields embeddings that are competitive on both molecular property prediction and scientific NLP tasks.