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20242026
most citedRecent Advances on Machine Learning for Computational Fluid Dynamics: A Survey

30 citations · 30 across the 6 of their papers we have counts for

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cs.LG2026

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…

cs.LG2025

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-…

cs.LG2025

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…

cs.LG202430 cited

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…

cs.LG2024

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…

cs.LG2024

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…