59 citations · 111 across the 16 of their papers we have counts for
5 papers · 1 filter
VoronoiPatches: Evaluating A New Data Augmentation Method
Steffen Illium, Gretchen Griffin, Michael Kölle +3
Overfitting is a problem in Convolutional Neural Networks (CNN) that causes poor generalization of models on unseen data. To remediate this problem, many new and diverse data augme…
Empirical Analysis of Limits for Memory Distance in Recurrent Neural Networks
Steffen Illium, Thore Schillman, Robert Müller +2
Common to all different kinds of recurrent neural networks (RNNs) is the intention to model relations between data points through time. When there is no immediate relationship betw…
Visual Transformers for Primates Classification and Covid Detection
Steffen Illium, Robert Müller, Andreas Sedlmeier +1
We apply the vision transformer, a deep machine learning model build around the attention mechanism, on mel-spectrogram representations of raw audio recordings. When adding mel-bas…
Constructing Organism Networks from Collaborative Self-Replicators
Steffen Illium, Maximilian Zorn, Cristian Lenta +3
We introduce organism networks, which function like a single neural network but are composed of several neural particle networks; while each particle network fulfils the role of a…
Case-Based Inverse Reinforcement Learning Using Temporal Coherence
Jonas Nüßlein, Steffen Illium, Robert Müller +2
Providing expert trajectories in the context of Imitation Learning is often expensive and time-consuming. The goal must therefore be to create algorithms which require as little ex…