Fig. 3
From: Domain adaptation of a SMILES chemical transformer to SELFIES with limited computational resources
Schematic of the feed-forward neural network used for QM9 regression. Embedding vectors (derived from ChemBERTa’s final-layer average pooling) are fed into sequential fully connected layers (512→256→128→64), each followed by batch normalization and dropout.
