2 citations · 2 across the 4 of their papers we have counts for
5 papers
Self-Supervised Amortized Neural Operators for Optimal Control: Scaling Laws and Applications
Wuzhe Xu, Jiequn Han, Rongjie Lai
Optimal control provides a principled framework for transforming dynamical system models into intelligent decision-making, yet classical computational approaches are often too expe…
Improving Data Fidelity via Diffusion Model-based Correction and Super-Resolution
Wuzhe Xu, Yulong Lu, Sifan Wang +1
We propose a unified diffusion model-based correction and super-resolution method to enhance the fidelity and resolution of diverse low-quality data through a two-step pipeline. Fi…
Diffusion-based Models for Unpaired Super-resolution in Fluid Dynamics
Wuzhe Xu, Yulong Lu, Lian Shen +2
High-fidelity, high-resolution numerical simulations are crucial for studying complex multiscale phenomena in fluid dynamics, such as turbulent flows and ocean waves. However, dire…
In-Context Learning of Linear Systems: Generalization Theory and Applications to Operator Learning
Frank Cole, Yulong Lu, Wuzhe Xu +1
We study theoretical guarantees for solving linear systems in-context using a linear transformer architecture. For in-domain generalization, we provide neural scaling laws that bou…
Generative downscaling of PDE solvers with physics-guided diffusion models
Yulong Lu, Wuzhe Xu
Solving partial differential equations (PDEs) on fine spatio-temporal scales for high-fidelity solutions is critical for numerous scientific breakthroughs. Yet, this process can be…