9 citations · 25 across the 10 of their papers we have counts for
3 papers · 1 filter
POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning
Frederik Schubert, Carolin Benjamins, Sebastian Döhler +2
The goal of Unsupervised Reinforcement Learning (URL) is to find a reward-agnostic prior policy on a task domain, such that the sample-efficiency on supervised downstream tasks is…
ChimeraMix: Image Classification on Small Datasets via Masked Feature Mixing
Christoph Reinders, Frederik Schubert, Bodo Rosenhahn
Deep convolutional neural networks require large amounts of labeled data samples. For many real-world applications, this is a major limitation which is commonly treated by augmenta…
Contextualize Me -- The Case for Context in Reinforcement Learning
Carolin Benjamins, Theresa Eimer, Frederik Schubert +6
While Reinforcement Learning ( RL) has made great strides towards solving increasingly complicated problems, many algorithms are still brittle to even slight environmental changes.…