2 papers
stat.ML2025
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…
cs.CR2024
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…