7 citations · 7 across the 12 of their papers we have counts for
15 papers
Direct Topology Tracking in Continuous Implicit Models
Guanqun Ma, David Lenz, Kaiyuan Tang +4
We present a framework for tracking topological features directly within continuous implicit models. Such models, including implicit neural representations (INRs) and multivariate…
Topology-Preserving Meshing of Implicit Scalar Fields via Monotonicity Constraints
Tanner Finken, Jixian Li, Bei Wang +2
Topological analysis of scalar fields yields structures such as the Morse-Smale complex (MSC) that summarize salient features across multiple scales. Existing MSC extraction algori…
FaCTz: Fast Critical-Point and Topology-Aware GPU Compression for Scientific Vector Fields
Mingze Xia, Yuxiao Li, Sheng Di +6
Error-bounded lossy compression is essential for storing and transferring the vector-field data produced by large-scale scientific simulations. Although it enforces a user-specifie…
FZ-VIS: A Visual Analytics Framework for Quantities-of-Interest-Aware Scientific Lossy Compression
Guoxi Liu, Yuxiao Li, Congrong Ren +6
Modern scientific simulations generate massive volumes of data, making lossy compression essential for efficient storage and transmission. However, preserving critical quantities o…
pMSz: A Distributed Parallel Algorithm for Correcting Extrema and Morse Smale Segmentations in Lossy Compression
Yuxiao Li, Mingze Xia, Xin Liang +7
Lossy compression, widely used by scientists to reduce data from simulations, experiments, and observations, can distort features of interest even under bounded error. Such distort…
Spatiotemporal Detection and Uncertainty Visualization of Atmospheric Blocking Events
Mingzhe Li, Peer Nowack, Bei Wang
Atmospheric blocking events are quasi-stationary high-pressure systems that disrupt the typical paths of polar and subtropical air currents, often producing prolonged extreme weath…
Time-varying Vector Field Compression with Preserved Critical Point Trajectories
Mingze Xia, Yuxiao Li, Pu Jiao +3
Scientific simulations and observations are producing vast amounts of time-varying vector field data, making it hard to store them for archival purposes and transmit them for analy…
TFZ: Topology-Preserving Compression of 2D Symmetric and Asymmetric Second-Order Tensor Fields
Nathaniel Gorski, Xin Liang, Hanqi Guo +1
In this paper, we present a novel compression framework, TFZ, that preserves the topology of 2D symmetric and asymmetric second-order tensor fields defined on flat triangular meshe…
Extracting Complex Topology from Multivariate Functional Approximation: Contours, Jacobi Sets, and Ridge-Valley Graphs
Guanqun Ma, David Lenz, Hanqi Guo +2
Implicit continuous models, such as functional models and implicit neural networks, are an increasingly popular method for replacing discrete data representations with continuous,…
ChannelExplorer: Exploring Class Separability Through Activation Channel Visualization
Md Rahat-uz- Zaman, Bei Wang, Paul Rosen
Deep neural networks (DNNs) achieve state-of-the-art performance in many vision tasks, yet understanding their internal behavior remains challenging, particularly how different lay…
A General Framework for Augmenting Lossy Compressors with Topological Guarantees
Nathaniel Gorski, Xin Liang, Hanqi Guo +2
Topological descriptors such as contour trees are widely utilized in scientific data analysis and visualization, with applications from materials science to climate simulations. It…
Preserving Discrete Morse-Smale Complexes in Error-Bounded Lossy Compression
Yuxiao Li, Mingze Xia, Xin Liang +2
Scientific applications are generating unprecedented volumes of data that overwhelm storage and transmission systems, posing significant challenges for the design of data managemen…
Critical Point Extraction from Multivariate Functional Approximation
Guanqun Ma, David Lenz, Tom Peterka +2
Advances in high-performance computing require new ways to represent large-scale scientific data to support data storage, data transfers, and data analysis within scientific workfl…
MSz: An Efficient Parallel Algorithm for Correcting Morse-Smale Segmentations in Error-Bounded Lossy Compressors
Yuxiao Li, Xin Liang, Bei Wang +3
This research explores a novel paradigm for preserving topological segmentations in existing error-bounded lossy compressors. Today's lossy compressors rarely consider preserving t…
Interactive Visualization of Time-Varying Flow Fields Using Particle Tracing Neural Networks
Mengjiao Han, Jixian Li, Sudhanshu Sane +4
In this paper, we present a comprehensive evaluation to establish a robust and efficient framework for Lagrangian-based particle tracing using deep neural networks (DNNs). Han et a…