6 citations · 6 across the 4 of their papers we have counts for
4 papers
Uncertainty Quantification for Physics-Informed Neural Networks with Extended Fiducial Inference
Frank Shih, Zhenghao Jiang, Faming Liang
Uncertainty quantification (UQ) in scientific machine learning is increasingly critical as neural networks are widely adopted to tackle complex problems across diverse scientific d…
Uncertainty Quantification of Deep Learning for Spatiotemporal Data: Challenges and Opportunities
Wenchong He, Zhe Jiang
With the advancement of GPS, remote sensing, and computational simulations, large amounts of geospatial and spatiotemporal data are being collected at an increasing speed. Such eme…
Deep Learning for Spatiotemporal Big Data: A Vision on Opportunities and Challenges
Zhe Jiang
With advancements in GPS, remote sensing, and computational simulation, an enormous volume of spatiotemporal data is being collected at an increasing speed from various application…
A Double-Linked Blockchain Approach Based on Proof-of-Refundable-Tax Consensus Algorithm
Zheng-Xun Jiang, Ren-Song Tsay
In this paper we propose a double-linked blockchain data structure that greatly improves blockchain performance and guarantees single chain with no forks. Additionally, with the pr…