5 papers
Exact ensemble controllability for neural differential equations via neural interpolation
Martin Gugat
We study a system that is governed by neural dynamics. Neural dynamics are a model for deep neural networks with a large number of layers. For a differential equation where the rig…
AI-supported Degradation Study of Carbon-based Perovskite Solar Cells: Learning the Device Physics of Perovskite Solar Cells: A Drift-Diffusion Guided Autoencoder Approach
Oliver Zbinden, Sharun Parayil Shaji, Wolfgang Tress
Carbon-electrode-based PSC devices are stressed under 1 Sun equivalent illumination in a stability setup, and different scan-speed dependent current-voltage (J-V) curves are measur…
De novo molecular structure elucidation from mass spectra via flow matching
Ghaith Mqawass, Tuan Le, Fabian Theis +1
Mass spectrometry is a powerful and widely used tool for identifying molecular structures due to its sensitivity and ability to profile complex samples. However, translating spectr…
MInDI-3D: Iterative Deep Learning in 3D for Sparse-view Cone Beam Computed Tomography
Daniel Barco, Marc Stadelmann, Martin Oswald +7
We present MInDI-3D (Medical Inversion by Direct Iteration in 3D), the first 3D conditional diffusion-based model for real-world sparse-view Cone Beam Computed Tomography (CBCT) ar…
Euclid: Early Release Observations of diffuse stellar structures and globular clusters as probes of the mass assembly of galaxies in the Dorado group
M. Urbano, P. -A. Duc, T. Saifollahi +160
Deep surveys reveal tidal debris and associated compact stellar systems. Euclid's unique combination of capabilities (spatial resolution, depth, and wide sky coverage) will make it…