Jannik Wiese — accepted AI-conference papers

2026

Envisioning the Future, One Step at a Time

Stefan Andreas Baumann, Jannik Wiese, Tommaso Martorella, Mahdi M. Kalayeh, Björn Ommer

CVPR 2026

Accurately anticipating how complex, diverse scenes will evolve requires models that represent uncertainty, simulate along extended interaction chains, and efficiently explore many plausible futures. Yet most existing approaches rely on dense video or latent-space prediction, expending substantial c

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2026

Probabilistic Precipitation Nowcasting with Rectified Flow Transformers

Johannes Schusterbauer, Jannik Wiese, Nick Stracke, Timy Phan, Björn Ommer

CVPR 2026

Accurate weather forecasts are essential across various domains and are safety-critical in extreme weather conditions. Compared to simulation-based forecasting, data-driven approaches show greater efficiency, enabling short-term, high-resolution nowcasting. In particular, diffusion models proved eff

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