213 citations · 316 across the 10 of their papers we have counts for
4 papers · 1 filter
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation
Haoyu Wang, Nan Wu, Hang Yang +2
Using machine learning to solve combinatorial optimization (CO) problems is challenging, especially when the data is unlabeled. This work proposes an unsupervised learning framewor…
GTNet: A Tree-Based Deep Graph Learning Architecture
Nan Wu, Chaofan Wang
We propose Graph Tree Networks (GTNets), a deep graph learning architecture with a new general message passing scheme that originates from the tree representation of graphs. In the…
High-Level Synthesis Performance Prediction using GNNs: Benchmarking, Modeling, and Advancing
Nan Wu, Hang Yang, Yuan Xie +2
Agile hardware development requires fast and accurate circuit quality evaluation from early design stages. Existing work of high-level synthesis (HLS) performance prediction usuall…
LOSTIN: Logic Optimization via Spatio-Temporal Information with Hybrid Graph Models
Nan Wu, Jiwon Lee, Yuan Xie +1
Despite the stride made by machine learning (ML) based performance modeling, two major concerns that may impede production-ready ML applications in EDA are stringent accuracy requi…