7 papers
TIDE: A Physically Diverse 3D Turbulence Benchmark Dataset for Advancing Scientific Machine Learning
Yilong Dai, Yiming Sun, Yiheng Chen +4
Turbulence is a central testbed for machine learning on physical dynamics because its governing laws are known exactly. However, most existing studies remain in 2D, while 3D turbul…
Physics-Preserving Latent Compression for Zero-Shot Resolution Transfer in 3D Turbulence
Yilong Dai, Yiming Sun, Yiheng Chen +4
High-resolution turbulence modeling is essential for scientific computing, but remains constrained by the cost of direct numerical simulation and the scarcity of full-resolution da…
Empowering LLM Agents with Geospatial Awareness: Toward Grounded Reasoning for Wildfire Response
Yiheng Chen, Lingyao Li, Zihui Ma +4
Effective disaster response is essential for safeguarding lives and property. Existing statistical approaches often lack semantic context, generalize poorly across events, and offe…
FlowRefiner: Flow Matching-Based Iterative Refinement for 3D Turbulent Flow Simulation
Yilong Dai, Yiming Sun, Yiheng Chen +3
Accurate autoregressive prediction of 3D turbulent flows remains challenging for neural PDE solvers, as small errors in fine-scale structures can accumulate rapidly over rollout. I…
When Earth Foundation Models Meet Diffusion: An Application to Land Surface Temperature Super-Resolution
Yiheng Chen, Zihui Ma, Peishi Jiang +6
Land surface temperature (LST) super-resolution is important for environmental monitoring. However, it remains challenging as coarse thermal observations severely underdetermine fi…
Politicized Attention Shifts Amplify Polarization in the Information Ecosystem during California Wildfires
Yiheng Chen, Alina Hagen, Fan Yang +4
Wildfires require governments to communicate under conditions of urgency, uncertainty, and intense public scrutiny, yet such communication now unfolds within a digitally mediated e…