3 papers
cs.LG2026
Mamba Neural Operator: Who Wins? Transformers vs. State-Space Models for PDEs
Chun-Wun Cheng, Jiahao Huang, Yi Zhang +3
Partial differential equations (PDEs) are widely used to model complex physical systems, but solving them efficiently remains a significant challenge. Recently, Transformers have e…
cs.CV2026
ProSMA-UNet: Decoder Conditioning for Proximal-Sparse Skip Feature Selection
Chun-Wun Cheng, Yanqi Cheng, Peiyuan Jing +4
Medical image segmentation commonly relies on U-shaped encoder-decoder architectures such as U-Net, where skip connections preserve fine spatial detail by injecting high-resolution…
cs.LG2024
HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
Andrey Bryutkin, Jiahao Huang, Zhongying Deng +3
We present a novel graph transformer framework, HAMLET, designed to address the challenges in solving partial differential equations (PDEs) using neural networks. The framework use…