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Unsupervised Representation Learning for Diverse Deformable Shape Collections
Sara Hahner, Souhaib Attaiki, Jochen Garcke +1
We introduce a novel learning-based method for encoding and manipulating 3D surface meshes. Our method is specifically designed to create an interpretable embedding space for defor…
In-situ Estimation of Time-averaging Uncertainties in Turbulent Flow Simulations
Saleh Rezaeiravesh, Christian Gscheidle, Adam Peplinski +2
The statistics obtained from turbulent flow simulations are generally uncertain due to finite time averaging. The techniques available in the literature to accurately estimate thes…
On minimizing the training set fill distance in machine learning regression
Paolo Climaco, Jochen Garcke
For regression tasks one often leverages large datasets for training predictive machine learning models. However, using large datasets may not be feasible due to computational limi…
On the Interplay of Subset Selection and Informed Graph Neural Networks
Niklas Breustedt, Paolo Climaco, Jochen Garcke +5
Machine learning techniques paired with the availability of massive datasets dramatically enhance our ability to explore the chemical compound space by providing fast and accurate…
Graph Extraction for Assisting Crash Simulation Data Analysis
Anahita Pakiman, Jochen Garcke, Axel Schumacher
In this work, we establish a method for abstracting information from Computer Aided Engineering (CAE) into graphs. Such graph representations of CAE data can improve design guideli…
Studying Evolutionary Solution Adaption Using a Flexibility Benchmark Based on a Metal Cutting Process
Leo Francoso Dal Piccol Sotto, Sebastian Mayer, Hemanth Janarthanam +2
We consider optimizing for different production requirements from the viewpoint of a bio-inspired framework for system flexibility that allows us to study the ability of an algorit…