Does Normalization Choice Matter for Causal Large Time-Series Models? 事件

Does Normalization Choice Matter for Causal Large Time-Series Models? arXiv:2606.09954v1 Announce Type: cross Abstract: Large models for time-series forecasting have been emerged as a promising paradigm for training models on heterogeneous collections of signals. These models typically rely on causal autoregressive architectures, where each observation is sequentially predicted from past. In practice, real-world time-series exhibit non-stationarities, which significantly influence predictive pe