TD-VAE

2000년 도입 · 논문 2편에서 사용

TD-VAE, or Temporal Difference VAE, is a generative sequence model that learns representations containing explicit beliefs about states several steps into the future, and that can be rolled out directly without single-step transitions. TD-VAE is trained on pairs of temporally separated time points, using an analogue of temporal difference learning used in reinforcement learning.

출처: Temporal Difference Variational Auto-Encoder

소개 논문: Temporal Difference Variational Auto-Encoder