Time-Series LLMs, Explained with t0-alpha
中文摘要
t0-alpha是用于概率时间序列预测的解码器式Patch Transformer，利用32步补丁和注意力机制预测未来分位数，而非单点预测。
English Summary
t0-alpha is a decoder-style patch transformer for probabilistic time-series forecasting. It uses 32-step patches and attention to predict future quantiles instead of single points.
原文节选
t0-alpha is a decoder-style patch transformer for probabilistic time-series forecasting. Raw series are split into 32-step patches, embedded, processed through causal time-attention and group-attention layers, and decoded into future quantiles rather than a single point forecast. The post Time-Series LLMs, Explained with t0-alpha appeared first on Towards Data Science.