101 citations · 255 across the 14 of their papers we have counts for
14 papers
Adaptively Placed Multi-Grid Scene Representation Networks for Large-Scale Data Visualization
Skylar Wolfgang Wurster, Tianyu Xiong, Han-Wei Shen +2
Scene representation networks (SRNs) have been recently proposed for compression and visualization of scientific data. However, state-of-the-art SRNs do not adapt the allocation of…
TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones
Lin Yan, Hanqi Guo, Thomas Peterka +2
Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks.…
Neural Stream Functions
Skylar Wolfgang Wurster, Hanqi Guo, Tom Peterka +1
We present a neural network approach to compute stream functions, which are scalar functions with gradients orthogonal to a given vector field. As a result, isosurfaces of the stre…
TopoSZ: Preserving Topology in Error-Bounded Lossy Compression
Lin Yan, Xin Liang, Hanqi Guo +1
Existing error-bounded lossy compression techniques control the pointwise error during compression to guarantee the integrity of the decompressed data. However, they typically do n…
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…
Reinforcement Learning for Load-balanced Parallel Particle Tracing
Jiayi Xu, Hanqi Guo, Han-Wei Shen +3
We explore an online reinforcement learning (RL) paradigm to dynamically optimize parallel particle tracing performance in distributed-memory systems. Our method combines three nov…
Exact Analytical Parallel Vectors
Hanqi Guo, Tom Peterka
This paper demonstrates that parallel vector curves are piecewise cubic rational curves in 3D piecewise linear vector fields. Parallel vector curves -- loci of points where two vec…
Deep Hierarchical Super Resolution for Scientific Data
Skylar W. Wurster, Hanqi Guo, Han-Wei Shen +2
We present a novel technique for hierarchical super resolution (SR) with neural networks (NNs), which upscales volumetric data represented with an octree data structure to a high-r…
FTK: A Simplicial Spacetime Meshing Framework for Robust and Scalable Feature Tracking
Hanqi Guo, David Lenz, Jiayi Xu +7
We present the Feature Tracking Kit (FTK), a framework that simplifies, scales, and delivers various feature-tracking algorithms for scientific data. The key of FTK is our high-dim…
Asynchronous and Load-Balanced Union-Find for Distributed and Parallel Scientific Data Visualization and Analysis
Jiayi Xu, Hanqi Guo, Han-Wei Shen +5
We present a novel distributed union-find algorithm that features asynchronous parallelism and k-d tree based load balancing for scalable visualization and analysis of scientific d…
Microparticle cloud imaging and tracking for data-driven plasma science
Zhehui Wang, Jiayi Xu, Yao E. Kovach +5
Large data sets give rise to the `fourth paradigm' of scientific discovery and technology development, extending other approaches based on human intuition, fundamental laws of phys…
InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations
Wenbin He, Junpeng Wang, Hanqi Guo +5
We propose InSituNet, a deep learning based surrogate model to support parameter space exploration for ensemble simulations that are visualized in situ. In situ visualization, gene…
Z-checker: A Framework for Assessing Lossy Compression of Scientific Data
Dingwen Tao, Sheng Di, Hanqi Guo +2
Because of vast volume of data being produced by today's scientific simulations and experiments, lossy data compressor allowing user-controlled loss of accuracy during the compress…