Introduces PVMC, a parallelizable training method for deep state space models that claims state-of-the-art results and 10x faster training than prior SMC approaches.
For PVMC, DMM, and P-V AE we decrease the suppression from a factor of 0.05 to 1 over the course of training
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Efficient Learning of Deep State Space Models via Importance Smoothing
Introduces PVMC, a parallelizable training method for deep state space models that claims state-of-the-art results and 10x faster training than prior SMC approaches.