4 citations · 4 across the 1 of their papers we have counts for
5 papers
Active Subspace of Neural Networks: Structural Analysis and Universal Attacks
Chunfeng Cui, Kaiqi Zhang, Talgat Daulbaev +3
Active subspace is a model reduction method widely used in the uncertainty quantification community. In this paper, we propose analyzing the internal structure and vulnerability an…
Tensor Methods for Generating Compact Uncertainty Quantification and Deep Learning Models
Chunfeng Cui, Cole Hawkins, Zheng Zhang
Tensor methods have become a promising tool to solve high-dimensional problems in the big data era. By exploiting possible low-rank tensor factorization, many high-dimensional mode…
Chance-Constrained and Yield-aware Optimization of Photonic ICs with Non-Gaussian Correlated Process Variations
Chunfeng Cui, Kaikai Liu, Zheng Zhang
Uncertainty quantification has become an efficient tool for uncertainty-aware prediction, but its power in yield-aware optimization has not been well explored from either theoretic…
Efficient Uncertainty Modeling for System Design via Mixed Integer Programming
Zichang He, Weilong Cui, Chunfeng Cui +2
The post-Moore era casts a shadow of uncertainty on many aspects of computer system design. Managing that uncertainty requires new algorithmic tools to make quantitative assessment…
High-Dimensional Uncertainty Quantification of Electronic and Photonic IC with Non-Gaussian Correlated Process Variations
Chunfeng Cui, Zheng Zhang
Uncertainty quantification based on generalized polynomial chaos has been used in many applications. It has also achieved great success in variation-aware design automation. Howeve…