6 citations · 20 across the 10 of their papers we have counts for
20 papers
RMFGP: Rotated Multi-fidelity Gaussian process with Dimension Reduction for High-dimensional Uncertainty Quantification
Jiahao Zhang, Shiqi Zhang, Guang Lin
Multi-fidelity modelling arises in many situations in computational science and engineering world. It enables accurate inference even when only a small set of accurate data is avai…
MultiAuto-DeepONet: A Multi-resolution Autoencoder DeepONet for Nonlinear Dimension Reduction, Uncertainty Quantification and Operator Learning of Forward and Inverse Stochastic Problems
Jiahao Zhang, Shiqi Zhang, Guang Lin
A new data-driven method for operator learning of stochastic differential equations(SDE) is proposed in this paper. The central goal is to solve forward and inverse stochastic prob…
PAGP: A physics-assisted Gaussian process framework with active learning for forward and inverse problems of partial differential equations
Jiahao Zhang, Shiqi Zhang, Guang Lin
In this work, a Gaussian process regression(GPR) model incorporated with given physical information in partial differential equations(PDEs) is developed: physics-assisted Gaussian…
Reasoning with Scene Graphs for Robot Planning under Partial Observability
Saeid Amiri, Kishan Chandan, Shiqi Zhang
Robot planning in partially observable domains is difficult, because a robot needs to estimate the current state and plan actions at the same time. When the domain includes many ob…
DeepONet-Grid-UQ: A Trustworthy Deep Operator Framework for Predicting the Power Grid's Post-Fault Trajectories
Christian Moya, Shiqi Zhang, Meng Yue +1
This paper proposes a new data-driven method for the reliable prediction of power system post-fault trajectories. The proposed method is based on the fundamentally new concept of D…
Effective and Scalable Clustering on Massive Attributed Graphs
Renchi Yang, Jieming Shi, Yin Yang +3
Given a graph G where each node is associated with a set of attributes, and a parameter k specifying the number of output clusters, k-attributed graph clustering (k-AGC) groups nod…