7 papers
SafeDivertor: Faithful Divertor Heat Flux Reconstruction from Macroscopic Plasma State Signals via Time-Frequency Prior Exploitation
Hao Si, Zehua Chen, Qingquan Yang +8
Divertor heat-flux analysis is essential for understanding plasma-wall interactions and protecting plasma-facing components in magnetic-confinement fusion devices, while convention…
Temperature Field Reconstruction of Tungsten Monoblock Divertor on EAST using Physics-aware Neural Operator Transformer
Zikang Yan, Xiao Wang, Qingquan Yang +6
Accurate modeling of the divertor temperature field is essential for preventing material melting and damage and for extending the service life of fusion devices. However, conventio…
UniPINN: A Unified PINN Framework for Multi-task Learning of Diverse Navier-Stokes Equations
Dengdi Sun, Jie Chen, Xiao Wang +1
Physics-Informed Neural Networks (PINNs) have shown promise in solving incompressible Navier-Stokes equations, yet existing approaches are predominantly designed for single-flow se…
HGTS-Former: Hierarchical HyperGraph Transformer for Multivariate Time Series Analysis
Hao Si, Xiao Wang, Fan Zhang +5
Multivariate time series analysis has long been one of the key research topics in the field of artificial intelligence. However, analyzing complex time series data remains a challe…
NESTOR: A Nested MOE-based Neural Operator for Large-Scale PDE Pre-Training
Dengdi Sun, Xiaoya Zhou, Xiao Wang +4
Neural operators have emerged as an efficient paradigm for solving PDEs, overcoming the limitations of traditional numerical methods and significantly improving computational effic…
EMRRG: Efficient Fine-Tuning Pre-trained X-ray Mamba Networks for Radiology Report Generation
Mingzheng Zhang, Jinfeng Gao, Dan Xu +5
X-ray image-based medical report generation (MRG) is a pivotal area in artificial intelligence that can significantly reduce diagnostic burdens for clinicians and patient wait time…