A self-supervised graph encoder for device-level circuits improves prediction of circuit similarity, delays, and op-amp performance across analog and digital designs.
Accurate prediction of molecular properties and drug targets using a self- supervised image representation learning framework
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DICE: Device-level Integrated Circuits Encoder with Graph Contrastive Pretraining
A self-supervised graph encoder for device-level circuits improves prediction of circuit similarity, delays, and op-amp performance across analog and digital designs.