We generalize the 'bits back with ANS' method to time-series models with a latent Markov structure. This family of models includes hidden Markov models (HMMs), linear Gaussian state space models (LGSSMs) and many more. We provide experimental evidence that our method is effective for small scale models, and discuss its applicability to larger scale settings such as video compression.

翻译：我们将“ 与 ANS 回溯比特” 的方法概括为具有潜伏的 Markov 结构的时间序列模型。 这组模型包括隐藏的 Markov 模型( MMS ) 、 线性高西亚国家空间模型( LGSSMs ) 以及更多的模型。 我们提供实验性证据,证明我们的方法对小型模型有效,并讨论其是否适用于视频压缩等大型设置。