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20242026
most citedLatent Knowledge-Guided Video Diffusion for Scientific Phenomena Generation from a Single Initial Frame

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

cs.AI2026

Beyond Equation Search: Conjecture-Guided Discovery with SCOPE and ClosureBench

Yuxiao Hu, Qian Li, Ding Wang +4

Most symbolic regression methods optimize candidate equations, but improving an equation's fit does not establish whether its underlying scientific conjecture should be retained, r…

cs.LG2026

DASS: A Solver-Adaptable Dynamic Auxiliary Search Strategy for Symbolic Regression

Yuxiao Hu, Qian Li, Ding Wang +3

Symbolic regression (SR) aims to discover interpretable mathematical expressions from data and plays a key role in scientific discovery. However, existing methods face a common bot…

physics.flu-dyn2025

Symbolic Regression-Enhanced Dynamic Wake Meandering: Fast and Physically Consistent Wind-Turbine Wake Modeling

Ding Wang, Dachuan Feng, Kangcheng Zhou +3

Accurately modeling wind turbine wakes is essential for optimizing wind farm performance but remains a persistent challenge. While the dynamic wake meandering (DWM) model captures…

cs.CV2024★ 1 cited

Latent Knowledge-Guided Video Diffusion for Scientific Phenomena Generation from a Single Initial Frame

Qinglong Cao, Xirui Li, Ding Wang +3

Video diffusion models have achieved impressive results in natural scene generation, yet they struggle to generalize to scientific phenomena such as fluid simulations and meteorolo…

physics.flu-dyn2024★ 1 cited

Discovering an interpretable mathematical expression for a full wind-turbine wake with artificial intelligence enhanced symbolic regression

Ding Wang, Yuntian Chen, Shiyi Chen

The rapid expansion of wind power worldwide underscores the critical significance of engineering-focused analytical wake models in both the design and operation of wind farms. Thes…