Deep Adaptive Arbitrary Polynomial Chaos Expansion: A Mini-data-driven Semi-supervised Method for Uncertainty Quantification

22 July 2021

Papers citing "Deep Adaptive Arbitrary Polynomial Chaos Expansion: A Mini-data-driven Semi-supervised Method for Uncertainty Quantification"

6 / 6 papers shown

Title
GenFormer: A Deep-Learning-Based Approach for Generating Multivariate Stochastic Processes Haoran Zhao Wayne Isaac Tan Uy AI4TS 27 0 0 03 Feb 2024
Uncertainty Guided Ensemble Self-Training for Semi-Supervised Global Field Reconstruction Yunyang Zhang Zhiqiang Gong Xiaoyu Zhao W. Yao AI4CE 36 2 0 23 Feb 2023
Multi-fidelity surrogate modeling for temperature field prediction using deep convolution neural network Yunyang Zhang Zhiqiang Gong Weien Zhou Xiaoyu Zhao Xiaohu Zheng W. Yao AI4CE 23 24 0 17 Jan 2023
Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network Xu Liu W. Yao Xiaohu Zheng Yingchun Xu 11 7 0 15 Jun 2022
Consistency regularization-based Deep Polynomial Chaos Neural Network Method for Reliability Analysis Xiaohu Zheng W. Yao Yunyang Zhang Xiaoya Zhang 21 19 0 29 Mar 2022
Deeply learned face representations are sparse, selective, and robust Yi Sun Xiaogang Wang Xiaoou Tang CVBM 252 921 0 03 Dec 2014