2 papers
math.OC2025
Employing Deep Neural Operators for PDE control by decoupling training and optimization
Oliver G. S. Lundqvist, Fabricio Oliveira
Neural networks have been applied to control problems, typically by combining data, differential equation residuals, and objective costs in the training loss or by incorporating au…
math.OC2025
ICNN-enhanced 2SP: Leveraging input convex neural networks for solving two-stage stochastic programming
Yu Liu, Fabricio Oliveira, Jan Kronqvist
Two-stage stochastic programming (2SP) offers a basic framework for modelling decision-making under uncertainty, yet scalability remains a challenge due to the computational comple…