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...Neuralnetworktheory philipp christian petersen university of vienna april contents introduction classical approximation results by neural networks universality approximationrates basic operations reapproximationofdictionaries approximationofsmoothfunctions fast approximations with kolmogorov relunetworks linear nite elements and relu approximationofthesquarefunction theroleofdepth representation compactly supported functions numberofpieces approximationofnon linearfunctions highdimensionalapproximation curseofdimensionality hierarchy assumptions manifoldassumptions dimensiondependentregularityassumption complexityofsetsofnetworks thegrowthfunctionandthevcdimension lowerboundsonapproximationrates spacesofrealisations networkspacesarenotconvex networkspacesarenotclosed in these notes we study a mathematical structure called objects have recently received muchattentionandhavebecomeacentralconceptinmodernmachinelearning historically however they weremotivatedbythefunctionalityofthehumanbra...