Sundial (Timer 3.0) 🚩 News (2025.08) Sundial has been integrated into Apache IoTDB, a native time series database. 🚩 News (2025.06) Sundial has been accepted as ICML 2025 Oral (Top 1%). 🚩 News (2025.05) Get 1st MASE on the GIFT Eval Benchmark. 🚩 News (2025.02) Get 1st MSE/MAE zero shot performance on Time Series Library datasets. Sundial is a family of generative time series foundation models. This version is pre trained on 1 trillion time points with 128M parameters. For more information, please refer to this paper. [[Slides]](https://cloud.tsinghua.edu.cn/f/8d526337afde465e87c9/) [[Poster]](https://cloud.tsinghua.edu.cn/f/cc2a156315e9453f99b3/) [[Intro (CN)]](https://mp.weixin.qq.com/s/y3sc2e2lmW1sqfnoK ZdDA). The model can make zero shot predictions for point and probabilistic forecasting. Not only the mean or quantiles, you can get any statistical predictions with a set of generated samples. Sundial can be viewed as an ARMA model (Auto Regression and Moving Average). Transformer learns auto regressive token representations. Conditioned on them, TimeFlow transforms random noises into non deterministic predictions. Overall Architecture : The input time series is divided into…
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