NEURO-EVOLUTION OF CONTINUOUS-TIME DYNAMIC PROCESS CONTROLLERS

Neuro-Evolution of Continuous-Time Dynamic Process Controllers

Artificial neural networks are means which are, among several other approaches, effectively usable for modelling and control of non-linear dynamic systems.In case of modelling systems input and output signals are a-priori known, supervised learning methods can be used.But in case of controller design of dynamic systems the required (optimal) contro

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Optimizing ZX-diagrams with deep reinforcement learning

ZX-diagrams are a powerful graphical language for the description of quantum processes with applications in fundamental quantum mechanics, quantum circuit optimization, tensor network simulation, and many more.The utility of ZX-diagrams relies on a set of local transformation rules that can be applied to them without changing the underlying quantum

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A real life use of ruxolitinib in patients with acute and chronic graft versus host disease refractory to corticosteroid treatment in Latin American patients

Introduction: Graft-versus-host disease (GVHD) is a serious complication in allogeneic transplantation.The first-line treatment is high doses of corticosteroids.In the absence of response to corticosteroids, several immunosuppressive drugs can be used, but they entail an elevated risk of severe infections.Added to this, there are patients who do no

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