4 papers
Adversarial Reverse Mapping of Equilibrated Condensed-Phase Molecular Structures
Marc Stieffenhofer, Michael Wand, Tristan Bereau
A tight and consistent link between resolutions is crucial to further expand the impact of multiscale modeling for complex materials. We herein tackle the generation of condensed m…
Deep Non-Line-of-Sight Reconstruction
Javier Grau Chopite, Matthias B. Hullin, Michael Wand +1
The recent years have seen a surge of interest in methods for imaging beyond the direct line of sight. The most prominent techniques rely on time-resolved optical impulse responses…
Progressive Stochastic Binarization of Deep Networks
David Hartmann, Michael Wand
A plethora of recent research has focused on improving the memory footprint and inference speed of deep networks by reducing the complexity of (i) numerical representations (for ex…
Precomputed Real-Time Texture Synthesis with Markovian Generative Adversarial Networks
Chuan Li, Michael Wand
This paper proposes Markovian Generative Adversarial Networks (MGANs), a method for training generative neural networks for efficient texture synthesis. While deep neural network a…