22 citations · 42 across the 10 of their papers we have counts for
10 papers
Seeking the Yield Barrier: High-Dimensional SRAM Evaluation Through Optimal Manifold
Yanfang Liu, Guohao Dai, Wei W. Xing
Being able to efficiently obtain an accurate estimate of the failure probability of SRAM components has become a central issue as model circuits shrink their scale to submicrometer…
Differentiable Multi-Fidelity Fusion: Efficient Learning of Physics Simulations with Neural Architecture Search and Transfer Learning
Yuwen Deng, Wang Kang, Wei W. Xing
With rapid progress in deep learning, neural networks have been widely used in scientific research and engineering applications as surrogate models. Despite the great success of ne…
GAR: Generalized Autoregression for Multi-Fidelity Fusion
Yuxin Wang, Zheng Xing, Wei W. Xing
In many scientific research and engineering applications where repeated simulations of complex systems are conducted, a surrogate is commonly adopted to quickly estimate the whole…
High-Dimensional Yield Estimation using Shrinkage Deep Features and Maximization of Integral Entropy Reduction
Shuo Yin, Guohao Dai, Wei W. Xing
Despite the fast advances in high-sigma yield analysis with the help of machine learning techniques in the past decade, one of the main challenges, the curse of dimensionality, whi…
Residual Gaussian Process: A Tractable Nonparametric Bayesian Emulator for Multi-fidelity Simulations
Wei W. Xing, Akeel A. Shah, Peng Wang +2
Challenges in multi-fidelity modeling relate to accuracy, uncertainty estimation and high-dimensionality. A novel additive structure is introduced in which the highest fidelity sol…
Multi-Fidelity Bayesian Optimization via Deep Neural Networks
Shibo Li, Wei Xing, Mike Kirby +1
Bayesian optimization (BO) is a popular framework to optimize black-box functions. In many applications, the objective function can be evaluated at multiple fidelities to enable a…