History Compression via Language Models in Reinforcement Learning

1 code implementation • 24 May 2022 • Fabian Paischer, Thomas Adler, Vihang Patil, Angela Bitto-Nemling, Markus Holzleitner, Sebastian Lehner, Hamid Eghbal-zadeh, Sepp Hochreiter

In a partially observable Markov decision process (POMDP), an agent typically uses a representation of the past to approximate the underlying MDP.

reinforcement-learning

Cross-Domain Few-Shot Learning by Representation Fusion

2 code implementations • 13 Oct 2020 • Thomas Adler, Johannes Brandstetter, Michael Widrich, Andreas Mayr, David Kreil, Michael Kopp, Günter Klambauer, Sepp Hochreiter

On the few-shot datasets miniImagenet and tieredImagenet with small domain shifts, CHEF is competitive with state-of-the-art methods.

cross-domain few-shot learning Drug Discovery

Hopfield Networks is All You Need

2 code implementations • ICLR 2021 • Hubert Ramsauer, Bernhard Schäfl, Johannes Lehner, Philipp Seidl, Michael Widrich, Thomas Adler, Lukas Gruber, Markus Holzleitner, Milena Pavlović, Geir Kjetil Sandve, Victor Greiff, David Kreil, Michael Kopp, Günter Klambauer, Johannes Brandstetter, Sepp Hochreiter

The new update rule is equivalent to the attention mechanism used in transformers.

Immune Repertoire Classification Multiple Instance Learning

Quantum Optical Experiments Modeled by Long Short-Term Memory

no code implementations • 30 Oct 2019 • Thomas Adler, Manuel Erhard, Mario Krenn, Johannes Brandstetter, Johannes Kofler, Sepp Hochreiter

In this work, we show that machine learning models can provide significant improvement over random search.

Patch Refinement -- Localized 3D Object Detection

no code implementations • 9 Oct 2019 • Johannes Lehner, Andreas Mitterecker, Thomas Adler, Markus Hofmarcher, Bernhard Nessler, Sepp Hochreiter

We introduce Patch Refinement a two-stage model for accurate 3D object detection and localization from point cloud data.

3D Object Detection Region Proposal