7 citations · 14 across the 6 of their papers we have counts for
6 papers
Towards Deep Active Learning in Avian Bioacoustics
Lukas Rauch, Denis Huseljic, Moritz Wirth +3
Passive acoustic monitoring (PAM) in avian bioacoustics enables cost-effective and extensive data collection with minimal disruption to natural habitats. Despite advancements in co…
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…
Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation
Diego Botache, Jens Decke, Winfried Ripken +4
This paper presents a methodological framework for training, self-optimising, and self-organising surrogate models to approximate and speed up multiobjective optimisation of techni…
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…
Dataset of a parameterized U-bend flow for Deep Learning Applications
Jens Decke, Olaf Wünsch, Bernhard Sick
This dataset contains 10,000 fluid flow and heat transfer simulations in U-bend shapes. Each of them is described by 28 design parameters, which are processed with the help of Comp…