30 citations · 35 across the 7 of their papers we have counts for
9 papers
Real-time Tokamak Equilibrium Reconstruction Under Limited Experimental Data via Physics-Grounded Synthetic Pre-training
Mingdong He, Qixian Hu, Tengfei Xu +2
Real-time equilibrium reconstruction is essential for tokamak plasma control. Data-driven surrogates are usually trained on high-quality labeled experimental data, but producing a…
SINO: Scale-Invariant Neural Operator
Kaichen Ouyang, Chenglei Yu, Chuanrui Wang +1
In scientific machine learning, physical fields governed by partial differential equations exhibit low-rank structure and scale invariance. When solving equations on coarse grids,…
Path Integral Value Matching for Linear Quadratic Stochastic Optimal Control
Bangyan Liao, Chenglei Yu, Yuchen Yang +4
Linear Quadratic Stochastic Optimal Control (LQ-SOC) establishes a fundamental framework for steering noisy dynamical systems and has recently gained renewed interest in the machin…
PACE: Geometry-Aware Bridge Transport for Single-Cell Trajectory Inference
Chenglei Yu, Chuanrui Wang, Bangyan Liao +1
Single-cell trajectory inference from destructive time-course snapshots is fundamentally ill-posed: neither cross-time cell correspondences nor continuous trajectories are observed…
FLDmamba: Integrating Fourier and Laplace Transform Decomposition with Mamba for Enhanced Time Series Prediction
Qianru Zhang, Chenglei Yu, Haixin Wang +5
Time series prediction, a crucial task across various domains, faces significant challenges due to the inherent complexities of time series data, including non-stationarity, multi-…
FourierFlow: Frequency-aware Flow Matching for Generative Turbulence Modeling
Haixin Wang, Jiashu Pan, Hao Wu +2
Modeling complex fluid systems, especially turbulence governed by partial differential equations (PDEs), remains a fundamental challenge in science and engineering. Recently, diffu…
Recent Advances on Machine Learning for Computational Fluid Dynamics: A Survey
Haixin Wang, Yadi Cao, Zijie Huang +13
This paper explores the recent advancements in enhancing Computational Fluid Dynamics (CFD) tasks through Machine Learning (ML) techniques. We begin by introducing fundamental conc…
A Survey of Generative Techniques for Spatial-Temporal Data Mining
Qianru Zhang, Haixin Wang, Cheng Long +8
This paper focuses on the integration of generative techniques into spatial-temporal data mining, considering the significant growth and diverse nature of spatial-temporal data. Wi…
BENO: Boundary-embedded Neural Operators for Elliptic PDEs
Haixin Wang, Jiaxin Li, Anubhav Dwivedi +2
Elliptic partial differential equations (PDEs) are a major class of time-independent PDEs that play a key role in many scientific and engineering domains such as fluid dynamics, pl…