Search Results for author:
Found 2 papers, 1 papers with code
DeepGate2: Functionality-Aware Circuit Representation Learning
Circuit representation learning aims to obtain neural representations of circuit elements and has emerged as a promising research direction that can be applied to various EDA and logic reasoning tasks.
The prediction of the quality of results in Logic Synthesis using Transformer and Graph Neural Networks
Furthermore, the Transformer and GNNs are adopted as a joint learning policy for the QoR prediction of the unseen circuit-optimization sequences.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
