1 citations · 2 across the 5 of their papers we have counts for
5 papers
Explorable INR: An Implicit Neural Representation for Ensemble Simulation Enabling Efficient Spatial and Parameter Exploration
Yi-Tang Chen, Haoyu Li, Neng Shi +3
With the growing computational power available for high-resolution ensemble simulations in scientific fields such as cosmology and oceanology, storage and computational demands pre…
ConfEviSurrogate: A Conformalized Evidential Surrogate Model for Uncertainty Quantification
Yuhan Duan, Xin Zhao, Neng Shi +1
Surrogate models, crucial for approximating complex simulation data across sciences, inherently carry uncertainties that range from simulation noise to model prediction errors. Wit…
VDL-Surrogate: A View-Dependent Latent-based Model for Parameter Space Exploration of Ensemble Simulations
Neng Shi, Jiayi Xu, Haoyu Li +3
We propose VDL-Surrogate, a view-dependent neural-network-latent-based surrogate model for parameter space exploration of ensemble simulations that allows high-resolution visualiza…
GNN-Surrogate: A Hierarchical and Adaptive Graph Neural Network for Parameter Space Exploration of Unstructured-Mesh Ocean Simulations
Neng Shi, Jiayi Xu, Skylar W. Wurster +4
We propose GNN-Surrogate, a graph neural network-based surrogate model to explore the parameter space of ocean climate simulations. Parameter space exploration is important for dom…
CNNs based Viewpoint Estimation for Volume Visualization
Neng Shi, Yubo Tao
Viewpoint estimation from 2D rendered images is helpful in understanding how users select viewpoints for volume visualization and guiding users to select better viewpoints based on…