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Marius Zöllner

2 accepted papers

2022

Point Cloud Generation with Continuous Conditioning

AISTATS 2022poster

Generative models can be used to synthesize 3D objects of high quality and diversity. However, there is typically no control over the properties of the generated object.This paper proposes a novel generative adversarial network (GAN) setup that generates 3D point cloud shapes conditioned on a contin…

2021

Sample-Specific Output Constraints for Neural Networks

AAAI 2021technical

It is common practice to constrain the output space of a neural network with the final layer to a problem-specific value range. However, for many tasks it is desired to restrict the output space for each input independently to a different subdomain with a non-trivial geometry, e.g. in safety-critica…