From the 1 of 4 linked papers with an AI index.
4 papers
Schrödinger's Cat: Probabilistic Representation and Prediction of Potential Scene Kinematics
Timy Phan, Jannik Wiese, Björn Ommer
The paper introduces GARFIELD, a probabilistic model that learns a structured spatio‑temporal latent representation of possible future scene motions from a single image and optiona…
Probabilistic Precipitation Nowcasting with Rectified Flow Transformers
Johannes Schusterbauer, Jannik Wiese, Nick Stracke +2
Accurate weather forecasts are essential across various domains and are safety-critical in extreme weather conditions. Compared to simulation-based forecasting, data-driven approac…
Envisioning the Future, One Step at a Time
Stefan Andreas Baumann, Jannik Wiese, Tommaso Martorella +2
Accurately anticipating how complex, diverse scenes will evolve requires models that represent uncertainty, simulate along extended interaction chains, and efficiently explore many…
Masked Conditioning for Deep Generative Models
Phillip Mueller, Jannik Wiese, Sebastian Mueller +1
Datasets in engineering domains are often small, sparsely labeled, and contain numerical as well as categorical conditions. Additionally. computational resources are typically limi…