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Found 3 papers, 3 papers with code
ChemBERTa-2: Towards Chemical Foundation Models
Large pretrained models such as GPT-3 have had tremendous impact on modern natural language processing by leveraging self-supervised learning to learn salient representations that can be used to readily finetune on a wide variety of downstream tasks.
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Molecular Property Prediction
on Clearance
Assigning Confidence to Molecular Property Prediction
Introduction: Computational modeling has rapidly advanced over the last decades, especially to predict molecular properties for chemistry, material science and drug design.
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction
GNNs and chemical fingerprints are the predominant approaches to representing molecules for property prediction.
