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cs.LG2025
DUE: A Deep Learning Framework and Library for Modeling Unknown Equations
Junfeng Chen, Kailiang Wu, Dongbin Xiu
Equations, particularly differential equations, are fundamental for understanding natural phenomena and predicting complex dynamics across various scientific and engineering discip…
cs.LG2024★ 2 cited
Positional Knowledge is All You Need: Position-induced Transformer (PiT) for Operator Learning
Junfeng Chen, Kailiang Wu
Operator learning for Partial Differential Equations (PDEs) is rapidly emerging as a promising approach for surrogate modeling of intricate systems. Transformers with the self-atte…
cs.LG2023★ 1 cited
Deep-OSG: Deep Learning of Operators in Semigroup
Junfeng Chen, Kailiang Wu
This paper proposes a novel deep learning approach for learning operators in semigroup, with applications to modeling unknown autonomous dynamical systems using time series data co…