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Found 2 papers, 2 papers with code
DE-HNN: An effective neural model for Circuit Netlist representation
Using the input and output data of the tools from past designs, one can attempt to build a machine learning model that predicts the outcome of a design in significantly shorter time than running the tool.
Less is More: Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits
In this work we propose HOGA, a novel attention-based model for learning circuit representations in a scalable and generalizable manner.
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