Update README.md

README.md

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 license: cc-by-nc-sa-4.0
+pipeline_tag: video-to-video
+tags:
+- weather
+- precipitation
+- nowcasting
 ---
+
+# Probabilistic Precipitation Nowcasting with Rectified Flow Transformers
+
+**TODO: badges**
+
+We propose FREUD, a FRame-wise Encoder, United Decoder rectified flow-based first stage for precipitation nowcasting.
+Weather forecasting requires probabilistic prediction. Our generative decoder allows **uncertainty-aware compression**.
+Our FREUD design enables variable-length inputs, robustness to frame drops, and preserves temporal consistency.
+We enable **simple training** - no loss weight tuning, only a simple, stable rectified flow objective.
+A rectified-flow model in FREUD latent space achieves **state-of-the-art distributional and perceptual forecasting** quality.
+
+![Reconstruction distributions for different precipitation levels](https://compvis.github.io/weather-rf/static/images/teaser_figure_weather.svg)
+*Our generative decoder can quantify uncertainty about compression and covers the true precipitation in heavy-rain scenarios, while deterministic decoding collapses to incorrect modes.*
+