1 citations · 1 across the 2 of their papers we have counts for
4 papers
A General and Streamlined Differentiable Optimization Framework
Andrew W. Rosemberg, Joaquim Dias Garcia, François Pacaud +5
Differentiating through constrained optimization problems is increasingly central to learning, control, and large-scale decision-making systems, yet practical integration remains c…
Nonlinear Optimization with GPU-Accelerated Neural Network Constraints
Robert Parker, Oscar Dowson, Nicole LoGiudice +2
We propose a reduced-space formulation for optimizing over trained neural networks where the network's outputs and derivatives are evaluated on a GPU. To do this, we treat the neur…
Transient Stability-Constrained OPF: Neural Network Surrogate Models and Pricing Stability
Manuel Garcia, Nicole LoGiudice, Robert Parker +1
A Transient Stability-Constrained Optimal Power Flow (TSC-OPF) problem is proposed that enforces frequency stability constraints using Neural Network (NN) surrogate models. NNs are…
Formulations and scalability of neural network surrogates in nonlinear optimization problems
Robert B. Parker, Oscar Dowson, Nicole LoGiudice +2
We compare full-space, reduced-space, and gray-box formulations for representing trained neural networks in nonlinear constrained optimization problems. We test these formulations…