PixelRNN and PixelCNN Pros: Improving PixelCNN performance Can explicitly compute likelihood - Gated convolutional layers p(x) Short-cut connections Explicit likelihood of training Discretized logistic loss data gives good evaluation Multi-scale metric Training tricks Good samples Etc.… Con: See Sequential generation =slow Van der Oord et al.NIPS 2016 Salimans et al.2017 (PixelCNN++) log.csdn.net/poulang5786 电子科技大学研究生《机器学习》电子科技大学研究生《机器学习》