HALO: Enhancing Time Series Generation via Hyperspherical Latents and Masked AutoregRessive Modeling
Most existing time series generators rely on a two-stage modeling paradigm: the first stage learns discrete latent representations of time series; the second stage performs autoregressive modeling on these discrete latents through next token prediction. However, this paradigm suffers from two stage-specific limitations...
Chun-Yi Hou, Xiangfei Qiu, Han-Yin Cheng et al.
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