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Philipp Grohs
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Philipp Grohs16 visible / 16 total nodes / 21 links

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Related contextCo-authorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipAuthorshipWorks onWorks onWorks onWorks onTopic signalTopic signalTopic signalPhilipp GrohsAPhilipp GrohsResearcherDavide NobileADavide NobileResearcherOn foundational discretization barriers in STFT phase retrievalWOn foundational discret...preprint / 2022Deep neural network approximations for Monte Carlo algorithmsWDeep neural network app...preprint / 2019Injectivity of Gabor phase retrieval from lattice measurementsWInjectivity of Gabor ph...preprint / 2022Lower bounds for artificial neural network approximations: A proof that shallow neural networks fail to overcome the curse of dimensionalityWLower bounds for artifi...preprint / 2021Deep neural network approximation for high-dimensional elliptic PDEs with boundary conditionsWDeep neural network app...preprint / 2020Phase Transitions in Rate Distortion Theory and Deep LearningWPhase Transitions in Ra...preprint / 2020Phase Retrieval: Uniqueness and StabilityWPhase Retrieval: Unique...preprint / 2020Continuous Shearlet Tight FramesWContinuous Shearlet Tig...preprint / 2010Definability and stability of multiscale decompositions for manifold-valued dataWDefinability and stabil...preprint / 2010Intrinsic Localization of Anisotropic Frames II: $α$-MoleculesWIntrinsic Localization ...preprint / 2014Cartoon Approximation with $α$-CurveletsWCartoon Approximation w...preprint / 2014$α$-MoleculesW$α$-Moleculespreprint / 2014math.OCTmath.OC9232 worksMachine LearningTMachine Learning49008 works
Person15 links

Philipp Grohs

Researcher

PersonDavide NobileCo-authorship / ResearcherPaperOn foundational discretization barriers in STFT phase retrievalAuthorship / preprint / 2022PaperDeep neural network approximations for Monte Carlo algorithmsAuthorship / preprint / 2019PaperInjectivity of Gabor phase retrieval from lattice measurementsAuthorship / preprint / 2022PaperLower bounds for artificial neural network approximations: A proof that shallow neural networks fail to overcome the curse of dimensionalityAuthorship / preprint / 2021PaperDeep neural network approximation for high-dimensional elliptic PDEs with boundary conditionsAuthorship / preprint / 2020PaperPhase Transitions in Rate Distortion Theory and Deep LearningAuthorship / preprint / 2020PaperPhase Retrieval: Uniqueness and StabilityAuthorship / preprint / 2020

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