2 citations · 2 across the 3 of their papers we have counts for
6 papers
NAS-Cap: Deep-Learning Driven 3-D Capacitance Extraction with Neural Architecture Search and Data Augmentation
Haoyuan Li, Dingcheng Yang, Chunyan Pei +1
More accurate capacitance extraction is demanded for designing integrated circuits under advanced process technology. The pattern matching approach and the field solver for capacit…
Algorithm xxx: Faster Randomized SVD with Dynamic Shifts
Xu Feng, Wenjian Yu, Yuyang Xie +1
Aiming to provide a faster and convenient truncated SVD algorithm for large sparse matrices from real applications (i.e. for computing a few of largest singular values and the corr…
SRAM-PG: Power Delivery Network Benchmarks from SRAM Circuits
Shan Shen, Zhiqiang Liu, Wenjian Yu
Designing the power delivery network (PDN) in very large-scale integrated (VLSI) circuits is increasingly important, especially for nowadays low-power integrated circuit (IC) desig…
Generating Adversarial Examples with Better Transferability via Masking Unimportant Parameters of Surrogate Model
Dingcheng Yang, Wenjian Yu, Zihao Xiao +1
Deep neural networks (DNNs) have been shown to be vulnerable to adversarial examples. Moreover, the transferability of the adversarial examples has received broad attention in rece…
Computing Effective Resistances on Large Graphs Based on Approximate Inverse of Cholesky Factor
Zhiqiang Liu, Wenjian Yu
Effective resistance, which originates from the field of circuits analysis, is an important graph distance in spectral graph theory. It has found numerous applications in various a…
Towards Lightweight and Automated Representation Learning System for Networks
Yuyang Xie, Jiezhong Qiu, Laxman Dhulipala +4
We propose LIGHTNE 2.0, a cost-effective, scalable, automated, and high-quality network embedding system that scales to graphs with hundreds of billions of edges on a single machin…