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cs.LG2026
Reachability and asymptotics of Gaussian Transformer dynamics
Albert Alcalde, Zhengping Ji, Enrique Zuazua
We formulate data propagation through the Transformer, the machine learning architecture powering large language models, as a nonlinear control system on the space of probability m…
cs.LG2025
Deep Neural ODE Operator Networks for PDEs
Ziqian Li, Kang Liu, Yongcun Song +2
Operator learning has emerged as a promising paradigm for developing efficient surrogate models to solve partial differential equations (PDEs). However, existing approaches often o…
cs.LG2025
Representation and Regression Problems in Neural Networks: Relaxation, Generalization, and Numerics
Kang Liu, Enrique Zuazua
In this work, we address three non-convex optimization problems associated with the training of shallow neural networks (NNs) for exact and approximate representation, as well as f…