8 citations · 10 across the 4 of their papers we have counts for
4 papers
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…
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…
Learning in Feedback-driven Recurrent Spiking Neural Networks using full-FORCE Training
Ankita Paul, Stefan Wagner, Anup Das
Feedback-driven recurrent spiking neural networks (RSNNs) are powerful computational models that can mimic dynamical systems. However, the presence of a feedback loop from the read…
Lessons Learned from the 1st ARIEL Machine Learning Challenge: Correcting Transiting Exoplanet Light Curves for Stellar Spots
Nikolaos Nikolaou, Ingo P. Waldmann, Angelos Tsiaras +20
The last decade has witnessed a rapid growth of the field of exoplanet discovery and characterisation. However, several big challenges remain, many of which could be addressed usin…