Search Results for author: Bernhard Schäfl

Found 4 papers, 2 papers with code

Hopular: Modern Hopfield Networks for Tabular Data

no code implementations29 Sep 2021 Bernhard Schäfl, Lukas Gruber, Angela Bitto-Nemling, Sepp Hochreiter

In experiments on small-sized tabular datasets with less than 1, 000 samples, Hopular surpasses Gradient Boosting, Random Forests, SVMs, and in particular several Deep Learning methods.

A GAN based solver of black-box inverse problems

no code implementations NeurIPS Workshop Deep_Invers 2019 Michael Gillhofer, Hubert Ramsauer, Johannes Brandstetter, Bernhard Schäfl, Sepp Hochreiter

We propose a GAN based approach to solve inverse problems which have non-differential or non-continuous forward relations.

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