17 citations · 74 across the 13 of their papers we have counts for
4 papers · 1 filter
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…
Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis
Diego Botache, Kristina Dingel, Rico Huhnstock +2
Splitting of sequential data, such as videos and time series, is an essential step in various data analysis tasks, including object tracking and anomaly detection. However, splitti…
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…