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000901967 1001_ $$0P:(DE-Juel1)159378$$aKegler, Philip$$b0$$eCorresponding author
000901967 245__ $$aChromium Doped UO2-Based Ceramics: Synthesis and Characterization of Model Materials for Modern Nuclear Fuels
000901967 260__ $$aBasel$$bMDPI$$c2021
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000901967 520__ $$aWe here unify the field-theoretical approach to neuronal networks with large deviations theory. For a prototypical random recurrent network model with continuous-valued units, we show that the effective action is identical to the rate function and derive the latter using field theory. This rate function takes the form of a Kullback-Leibler divergence which enables data-driven inference of model parameters and calculation of fluctuations beyond mean-field theory. Lastly, we expose a regime with fluctuation-induced transitions between mean-field solutions.
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000901967 7001_ $$0P:(DE-Juel1)130364$$aKlinkenberg, Martina$$b1
000901967 7001_ $$0P:(DE-Juel1)130329$$aBukaemskiy, Andrey$$b2$$ufzj
000901967 7001_ $$0P:(DE-Juel1)176900$$aMurphy, Gabriel L.$$b3
000901967 7001_ $$0P:(DE-Juel1)156511$$aDeissmann, Guido$$b4$$ufzj
000901967 7001_ $$0P:(DE-Juel1)144040$$aBrandt, Felix$$b5
000901967 7001_ $$0P:(DE-Juel1)130324$$aBosbach, Dirk$$b6$$ufzj
000901967 773__ $$0PERI:(DE-600)2487261-1$$a10.3390/ma14206160$$gVol. 14, no. 20, p. 6160 -$$n20$$p6160 -$$tMaterials$$v14$$x1996-1944$$y2021
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