most citedA Survey on Self-Supervised Representation Learning

8 citations · 12 across the 5 of their papers we have counts for

collaborators

5 papers

eess.IV2023

Limited-Angle Tomography Reconstruction via Deep End-To-End Learning on Synthetic Data

Thomas Germer, Jan Robine, Sebastian Konietzny +2

Computed tomography (CT) has become an essential part of modern science and medicine. A CT scanner consists of an X-ray source that is spun around an object of interest. On the opp…

cs.LG2023

Cyclophobic Reinforcement Learning

Stefan Sylvius Wagner, Peter Arndt, Jan Robine +1

In environments with sparse rewards, finding a good inductive bias for exploration is crucial to the agent's success. However, there are two competing goals: novelty search and sys…

cs.LG20238 cited

A Survey on Self-Supervised Representation Learning

Tobias Uelwer, Jan Robine, Stefan Sylvius Wagner +5

Learning meaningful representations is at the heart of many tasks in the field of modern machine learning. Recently, a lot of methods were introduced that allow learning of image r…

cs.LG20234 cited

Transformer-based World Models Are Happy With 100k Interactions

Jan Robine, Marc Höftmann, Tobias Uelwer +1

Deep neural networks have been successful in many reinforcement learning settings. However, compared to human learners they are overly data hungry. To build a sample-efficient worl…

cs.LG2023

Time-Myopic Go-Explore: Learning A State Representation for the Go-Explore Paradigm

Marc Höftmann, Jan Robine, Stefan Harmeling

Very large state spaces with a sparse reward signal are difficult to explore. The lack of a sophisticated guidance results in a poor performance for numerous reinforcement learning…