3 papers
physics.flu-dyn2026
Nested Fourier-enhanced neural operator for efficient modeling of radiation transfer in fires
Anran Jiao, Wengyao Jiang, Xiaoyi Lu +2
Computational fluid dynamics (CFD) has become an essential tool for predicting fire behavior, yet maintaining both efficiency and accuracy remains challenging. A major source of co…
cs.LG2025
TANTE: Time-Adaptive Operator Learning via Neural Taylor Expansion
Zhikai Wu, Sifan Wang, Shiyang Zhang +5
Operator learning for time-dependent partial differential equations (PDEs) has seen rapid progress in recent years, enabling efficient approximation of complex spatiotemporal dynam…
quant-ph2025
Quantum DeepONet: Neural operators accelerated by quantum computing
Pengpeng Xiao, Muqing Zheng, Anran Jiao +2
In the realm of computational science and engineering, constructing models that reflect real-world phenomena requires solving partial differential equations (PDEs) with different c…