59 citations · 111 across the 16 of their papers we have counts for
17 papers
Emergence in Multi-Agent Systems: A Safety Perspective
Philipp Altmann, Julian Schönberger, Steffen Illium +5
Emergent effects can arise in multi-agent systems (MAS) where execution is decentralized and reliant on local information. These effects may range from minor deviations in behavior…
Aquarium: A Comprehensive Framework for Exploring Predator-Prey Dynamics through Multi-Agent Reinforcement Learning Algorithms
Michael Kölle, Yannick Erpelding, Fabian Ritz +3
Recent advances in Multi-Agent Reinforcement Learning have prompted the modeling of intricate interactions between agents in simulated environments. In particular, the predator-pre…
Improving Primate Sounds Classification using Binary Presorting for Deep Learning
Michael Kölle, Steffen Illium, Maximilian Zorn +3
In the field of wildlife observation and conservation, approaches involving machine learning on audio recordings are becoming increasingly popular. Unfortunately, available dataset…
Compression of GPS Trajectories using Autoencoders
Michael Kölle, Steffen Illium, Carsten Hahn +3
The ubiquitous availability of mobile devices capable of location tracking led to a significant rise in the collection of GPS data. Several compression methods have been developed…
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…
Acoustic Leak Detection in Water Networks
Robert Müller, Steffen Illium, Fabian Ritz +4
In this work, we present a general procedure for acoustic leak detection in water networks that satisfies multiple real-world constraints such as energy efficiency and ease of depl…
Analysis of Feature Representations for Anomalous Sound Detection
Robert Müller, Steffen Illium, Fabian Ritz +1
In this work, we thoroughly evaluate the efficacy of pretrained neural networks as feature extractors for anomalous sound detection. In doing so, we leverage the knowledge that is…
Surgical Mask Detection with Convolutional Neural Networks and Data Augmentations on Spectrograms
Steffen Illium, Robert Müller, Andreas Sedlmeier +1
In many fields of research, labeled datasets are hard to acquire. This is where data augmentation promises to overcome the lack of training data in the context of neural network en…
Acoustic Anomaly Detection for Machine Sounds based on Image Transfer Learning
Robert Müller, Fabian Ritz, Steffen Illium +1
In industrial applications, the early detection of malfunctioning factory machinery is crucial. In this paper, we consider acoustic malfunction detection via transfer learning. Con…
Policy Entropy for Out-of-Distribution Classification
Andreas Sedlmeier, Robert Müller, Steffen Illium +1
One critical prerequisite for the deployment of reinforcement learning systems in the real world is the ability to reliably detect situations on which the agent was not trained. Su…
Trajectory annotation using sequences of spatial perception
Sebastian Feld, Steffen Illium, Andreas Sedlmeier +1
In the near future, more and more machines will perform tasks in the vicinity of human spaces or support them directly in their spatially bound activities. In order to simplify the…
Soccer Team Vectors
Robert Müller, Stefan Langer, Fabian Ritz +3
In this work we present STEVE - Soccer TEam VEctors, a principled approach for learning real valued vectors for soccer teams where similar teams are close to each other in the resu…
Deep Neural Baselines for Computational Paralinguistics
Daniel Elsner, Stefan Langer, Fabian Ritz +2
Detecting sleepiness from spoken language is an ambitious task, which is addressed by the Interspeech 2019 Computational Paralinguistics Challenge (ComParE). We propose an end-to-e…