Ensemble Distillation for Robust Model Fusion in Federated Learning

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The performance of magnetic confinement fusion devices, such as tokamaks, is strongly correlated to the phenomena that occur in the boundary region of the plasma core that faces the wall of the device. The dominant cross-field transport mechanisms from the ...

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The design point that had been chosen for EU DEMO in 2016 is reviewed here and a modification is proposed with a lower aspect ratio. Previously the same aspect ratio, A, was chosen for EU DEMO as in major tokamak experiments including ITER (A = 3.1), and, ...

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The implementation of three-dimensional magnetic fields, such as the ones of stellarators, in the GBS code (Ricci et al 2012 Plasma Phys. Control. Fusion54 124047; Giacomin et al 2022 J. Comput. Phys.464 111294) is presented, and simulation results are dis ...

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Neural network approaches to approximate the ground state of quantum hamiltonians require the numerical solution of a highly nonlinear optimization problem. We introduce a statistical learning approach that makes the optimization trivial by using kernel me ...

Ensemble Distillation for Robust Model Fusion in Federated Learning

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