1 citations · 1 across the 1 of their papers we have counts for
4 papers
Deep learning architectures for inference of AC-OPF solutions
Thomas Falconer, Letif Mones
We present a systematic comparison between neural network (NN) architectures for inference of AC-OPF solutions. Using fully connected NNs as a baseline we demonstrate the efficacy…
Learning an Optimally Reduced Formulation of OPF through Meta-optimization
Alex Robson, Mahdi Jamei, Cozmin Ududec +1
With increasing share of renewables in power generation mix, system operators would need to run Optimal Power Flow (OPF) problems closer to real-time to better manage uncertainty.…
Preconditioners for the geometry optimisation and saddle point search of molecular systems
Letif Mones, Gabor Csanyi, Christoph Ortner
A class of preconditioners is introduced to enhance geometry optimisation and transition state search of molecular systems. We start from the Hessian of molecular mechanical terms,…
A universal preconditioner for simulating condensed phase materials
David Packwood, James Kermode, Letif Mones +5
We introduce a universal sparse preconditioner that accelerates geometry optimisation and saddle point search tasks that are common in the atomic scale simulation of materials. Our…