papers

Publications (8)

eess.IV2025

Aneumo: A Large-Scale Multimodal Aneurysm Dataset with Computational Fluid Dynamics Simulations and Deep Learning Benchmarks

Xigui Li, Yuanye Zhou, Feiyang Xiao +16

Intracranial aneurysms (IAs) are serious cerebrovascular lesions found in approximately 5\% of the general population. Their rupture may lead to high mortality. Current methods for…

physics.ao-ph2024

FuXi-S2S: A machine learning model that outperforms conventional global subseasonal forecast models

Lei Chen, Xiaohui Zhong, Hao Li +8

Skillful subseasonal forecasts are crucial for various sectors of society but pose a grand scientific challenge. Recently, machine learning based weather forecasting models outperf…

cs.LG2023

FuXi-Extreme: Improving extreme rainfall and wind forecasts with diffusion model

Xiaohui Zhong, Lei Chen, Jun Liu +3

Significant advancements in the development of machine learning (ML) models for weather forecasting have produced remarkable results. State-of-the-art ML-based weather forecast mod…

physics.comp-ph2020

Operator learning for predicting multiscale bubble growth dynamics

Chensen Lin, Zhen Li, Lu Lu +3

Simulating and predicting multiscale problems that couple multiple physics and dynamics across many orders of spatiotemporal scales is a great challenge that has not been investiga…

cs.LG2026

Project and Generate: Divergence-Free Neural Operators for Incompressible Flows

Xigui Li, Hongwei Zhang, Ruoxi Jiang +6

Learning-based models for fluid dynamics often operate in unconstrained function spaces, leading to physically inadmissible, unstable simulations. While penalty-based methods offer…

cs.CV2025

Aneumo: A Large-Scale Comprehensive Synthetic Dataset of Aneurysm Hemodynamics

Xigui Li, Yuanye Zhou, Feiyang Xiao +10

Intracranial aneurysm (IA) is a common cerebrovascular disease that is usually asymptomatic but may cause severe subarachnoid hemorrhage (SAH) if ruptured. Although clinical practi…

physics.ao-ph2025

Terrain-aware Deep Learning for Wind Energy Applications: From Kilometer-scale Forecasts to Fine Wind Fields

Chensen Lin, Ruian Tie, Shihong Yi +2

High-resolution wind information is essential for wind energy planning and power forecasting, particularly in regions with complex terrain. However, most AI-based weather forecasti…

physics.flu-dyn2024

Bridging scales in multiscale bubble growth dynamics with correlated fluctuations using neural operator learning

Minglei Lu, Chensen Lin, Martian Maxey +2

The intricate process of bubble growth dynamics involves a broad spectrum of physical phenomena from microscale mechanics of bubble formation to macroscale interplay between bubble…