145 citations · 208 across the 11 of their papers we have counts for
11 papers
Active Transfer Prototypical Network: An Efficient Labeling Algorithm for Time-Series Data
Yuqicheng Zhu, Mohamed-Ali Tnani, Timo Jahnz +1
The paucity of labeled data is a typical challenge in the automotive industry. Annotating time-series measurements requires solid domain knowledge and in-depth exploratory data ana…
Outlier Detection using Self-Organizing Maps for Automated Blood Cell Analysis
Stefan Röhrl, Alice Hein, Lucie Huang +7
The quality of datasets plays a crucial role in the successful training and deployment of deep learning models. Especially in the medical field, where system performance may impact…
Analysis and Optimisation of Bellman Residual Errors with Neural Function Approximation
Martin Gottwald, Sven Gronauer, Hao Shen +1
Recent development of Deep Reinforcement Learning (DRL) has demonstrated superior performance of neural networks in solving challenging problems with large or even continuous state…
Interpretable PID Parameter Tuning for Control Engineering using General Dynamic Neural Networks: An Extensive Comparison
Johannes Günther, Elias Reichensdörfer, Patrick M. Pilarski +1
Modern automation systems rely on closed loop control, wherein a controller interacts with a controlled process, based on observations. These systems are increasingly complex, yet…
A Comparison of Prediction Algorithms and Nexting for Short Term Weather Forecasts
Michael Koller, Johannes Feldmaier, Klaus Diepold
This report first provides a brief overview of a number of supervised learning algorithms for regression tasks. Among those are neural networks, regression trees, and the recently…
The Virtuous Machine - Old Ethics for New Technology?
Nicolas Berberich, Klaus Diepold
Modern AI and robotic systems are characterized by a high and ever-increasing level of autonomy. At the same time, their applications in fields such as autonomous driving, service…
Evaluation of a RGB-LED-based Emotion Display for Affective Agents
Johannes Feldmaier, Tamara Marmat, Johannes Kuhn +1
Technology has become an essential part in every aspect of our lives. However the key to a successful implementation of a technology depends on the acceptance by the general public…
Regularized Gradient Temporal-Difference Learning
Dominik Meyer, Hao Shen, Klaus Diepold
In this paper, we study the Temporal Difference (TD) learning with linear value function approximation. It is well known that most TD learning algorithms are unstable with linear f…
Monitoring and Prediction in Smart Energy Systems via Multi-timescale Nexting
Johannes Feldmaier, Dominik Meyer, Hao Shen +1
Reliable prediction of system status is a highly demanded functionality of smart energy systems, which can enable users or human operators to react quickly to potential future syst…
Image Completion for View Synthesis Using Markov Random Fields and Efficient Belief Propagation
Julian Habigt, Klaus Diepold
View synthesis is a process for generating novel views from a scene which has been recorded with a 3-D camera setup. It has important applications in 3-D post-production and 2-D to…
Analysis Operator Learning and Its Application to Image Reconstruction
Simon Hawe, Martin Kleinsteuber, Klaus Diepold
Exploiting a priori known structural information lies at the core of many image reconstruction methods that can be stated as inverse problems. The synthesis model, which assumes th…