Robust DNN Surrogate Models with Uncertainty Quantification via Adversarial Training

no code implementations • 10 Nov 2022 • Lixiang Zhang, Jia Li

Furthermore, we adopt methods in adversarial training to enhance the robustness of DNN surrogate models.

Computational Efficiency Uncertainty Quantification

Deep Variable-Block Chain with Adaptive Variable Selection

no code implementations • 7 Dec 2019 • Lixiang Zhang, Lin Lin, Jia Li

In this paper, we propose a framework that imposes on blocks of variables a chain structure obtained by step-wise greedy search so that the DNN architecture can leverage the constructed grid.

Variable Selection