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We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...
In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Learning revolution, similarly to the way that Deep Learning revolutionized Computer Vision. To do so, we consider a variety of Computer-Aided Engineering pro ...
The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we p ...
The recent years have witnessed growing interest in the power of scientific visualization for simulation-based neuroscience. The research presented in this thesis develops methods to generate physically-realistic visualizations of neocortical models recons ...
Sufficient daylight exposure contributes to occupants' productivity and health in buildings. However, excessive daylight ingress induces discomfort glare and increases the cooling load in warm seasons. The performance of manual shading systems is limited b ...
In this article we develop function-based a posteriori error estimators for the solution of linear second order elliptic problems considering hierarchical spline spaces for the Galerkin discretization. We prove a global upper bound for the energy error. Th ...
MATHICSE2017
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Background: We present a software workflow capable of building large scale, highly detailed and realistic volumetric models of neocortical circuits from the morphological skeletons of their digitally reconstructed neurons. The limitations of the existing a ...
2017
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Constrained meshes play an important role in freeform architectural design, as they can represent panel layouts on freeform surfaces. It is challenging to perform realtime manipulation on such meshes, because all constraints need to be respected during the ...
2013
State-of-the-art density estimation methods for rendering participating media rely on a dense photon representation of the radiance distribution within a scene. A critical bottleneck of such kernel-based approaches is the excessive number of photons that a ...
Augmented reality in additive fabrication is predominantly applied to the manufacturing of structures from regularly shaped materials. Our work however embraces natural heterogeneity, by focusing on the assembly of irregularly shaped elements such as miner ...
