activity
20182022
most citedMachine Learning for Electronic Design Automation: A Survey

18 citations · 37 across the 7 of their papers we have counts for

collaborators

10 papers

cs.LG20222 cited

An Adversarial Active Sampling-based Data Augmentation Framework for Manufacturable Chip Design

Mingjie Liu, Haoyu Yang, Zongyi Li +7

Lithography modeling is a crucial problem in chip design to ensure a chip design mask is manufacturable. It requires rigorous simulations of optical and chemical models that are co…

cs.OH2022

Generic Lithography Modeling with Dual-band Optics-Inspired Neural Networks

Haoyu Yang, Zongyi Li, Kumara Sastry +6

Lithography simulation is a critical step in VLSI design and optimization for manufacturability. Existing solutions for highly accurate lithography simulation with rigorous models…

eess.SP202118 cited

Machine Learning for Electronic Design Automation: A Survey

Guyue Huang, Jingbo Hu, Yifan He +13

With the down-scaling of CMOS technology, the design complexity of very large-scale integrated (VLSI) is increasing. Although the application of machine learning (ML) techniques in…

cs.LG20212 cited

Routing Towards Discriminative Power of Class Capsules

Haoyu Yang, Shuhe Li, Bei Yu

Capsule networks are recently proposed as an alternative to modern neural network architectures. Neurons are replaced with capsule units that represent specific features or entitie…

cs.AR2020

DAMO: Deep Agile Mask Optimization for Full Chip Scale

Guojin Chen, Wanli Chen, Yuzhe Ma +2

Continuous scaling of the VLSI system leaves a great challenge on manufacturing and optical proximity correction (OPC) is widely applied in conventional design flow for manufactura…

cs.CR202015 cited

Attacking Split Manufacturing from a Deep Learning Perspective

Haocheng Li, Satwik Patnaik, Abhrajit Sengupta +5

The notion of integrated circuit split manufacturing which delegates the front-end-of-line (FEOL) and back-end-of-line (BEOL) parts to different foundries, is to prevent overproduc…