5 citations · 12 across the 8 of their papers we have counts for
8 papers
Predictions and Decision Making for Resilient Intelligent Sustainable Energy Systems
Martin Braun, Christian Gruhl, Christian A. Hans +7
Future energy systems are subject to various uncertain influences. As resilient systems they should maintain a constantly high operational performance whatever happens. We explore…
From Structured to Unstructured:A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs
Jens Decke, Olaf Wünsch, Bernhard Sick +1
This article investigates the application of computer vision and graph-based models in solving mesh-based partial differential equations within high-performance computing environme…
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing
Jens Decke, Arne Jenß, Bernhard Sick +1
This article presents the Sorting Composite Quantile Regression Neural Network (SCQRNN), an advanced quantile regression model designed to prevent quantile crossing and enhance com…
DADO -- Low-Cost Query Strategies for Deep Active Design Optimization
Jens Decke, Christian Gruhl, Lukas Rauch +1
In this experience report, we apply deep active learning to the field of design optimization to reduce the number of computationally expensive numerical simulations. We are interes…
Towards Organic Distribution Systems -- The Vision of Self-Configuring, Self-Organising, Self-Healing, and Self-Optimising Power Distribution Management
Inga Loeser, Martin Braun, Christian Gruhl +3
Due to the decarbonisation of energy use, the power system is expected to become the backbone of all energy sectors and thus the basic critical infrastructure. High penetration wit…
Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions
Christian Gruhl, Bernhard Sick
Hidden Markov Models (HMM) have been used for several years in many time series analysis or pattern recognitions tasks. HMM are often trained by means of the Baum-Welch algorithm w…
Towards Automation of Knowledge Understanding: An Approach for Probabilistic Generative Classifiers
Dominik Fisch, Christian Gruhl, Edgar Kalkowski +2
After data selection, pre-processing, transformation, and feature extraction, knowledge extraction is not the final step in a data mining process. It is then necessary to understan…
Detecting Novel Processes with CANDIES -- An Holistic Novelty Detection Technique based on Probabilistic Models
Christian Gruhl, Bernhard Sick
In this article, we propose CANDIES (Combined Approach for Novelty Detection in Intelligent Embedded Systems), a new approach to novelty detection in technical systems. We assume t…