The Oracle of DLphi

17 Jan 2019Dominik AlfkeWeston BainesJan BlechschmidtMauricio J. del Razo SarminaAmnon DroryDennis ElbrächterNando FarchminMatteo GambaraSilke GlasPhilipp GrohsPeter HinzDanijel KivaranovicChristian KümmerleGitta KutyniokSebastian LunzJan MacdonaldRyan MalthanerGregory NaisatAriel NeufeldPhilipp Christian PetersenRafael ReisenhoferJun-Da ShengLaura ThesingPhilipp TrunschkeJohannes von LindheimDavid WeberMelanie Weber

We present a novel technique based on deep learning and set theory which yields exceptional classification and prediction results. Having access to a sufficiently large amount of labelled training data, our methodology is capable of predicting the labels of the test data almost always even if the training data is entirely unrelated to the test data... (read more)

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