5 citations · 7 across the 2 of their papers we have counts for
2 papers
cs.LG2024★ 2 cited
Less is More: Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits
Chenhui Deng, Zichao Yue, Cunxi Yu +4
While graph neural networks (GNNs) have gained popularity for learning circuit representations in various electronic design automation (EDA) tasks, they face challenges in scalabil…
cs.LG2024★ 5 cited
Polynormer: Polynomial-Expressive Graph Transformer in Linear Time
Chenhui Deng, Zichao Yue, Zhiru Zhang
Graph transformers (GTs) have emerged as a promising architecture that is theoretically more expressive than message-passing graph neural networks (GNNs). However, typical GT model…