1 citations · 3 across the 12 of their papers we have counts for
5 papers · 1 filter
A Query-Efficient Stochastic Volume Rendering Framework for Time-Varying Implicit Neural Volumes
Alper Sahistan, Haichao Miao, Zhimin Li +3
Time-varying implicit neural representations (INRs) provide a compact representation of scientific volumes and, for modalities such as dynamic X-ray computed tomography (CT), are o…
Error Aware Distribution Prediction for Lightweight Implicit Neural Representations
Zhimin Li, Jake D. Balla, Joshua A. Levine
Implicit neural representations (INRs) offer compact encoding of volumes, but as lossy approximators, inevitably have prediction errors. We consider INRs that can simultaneously en…
Quantifying the Impact of Lossy Compression on Neural Generative Surrogate Modeling
Zhimin Li, Harshitha Menon, Charles Jekel +2
Neural networks are used as generative surrogate models for scientific discovery, which are trainable approximations of scientific simulations. These models enable users to replace…
Toward AI VIS Co-Scientists: A General and End-to-End Agent Harness for Solving Complex Data Visualization Tasks
Haichao Miao, Zhimin Li, Kuangshi Ai +4
The ability to inspect, interpret, and communicate complex data is crucial for virtually any scientific endeavor, but often requires significant expertise outside the core domain r…
Animating Petascale Time-varying Data on Commodity Hardware with LLM-assisted Scripting
Ishrat Jahan Eliza, Xuan Huang, Aashish Panta +4
Scientists face significant visualization challenges as time-varying datasets grow in speed and volume, often requiring specialized infrastructure and expertise to handle massive d…