Diffusion: Ho et al., 2020, arXiv:2006.11239 WaveGrad: Nanxin Chen et al.

David Bau et al., 2020, arXiv Keyword: Generative, Adversarial learning Problem: How to manipulate specific rules encoded by a deep generative model.

Stanislav Pidhorskyi et al., 2020, arXiv Keyword: Generative, Adversarial learning Problem: AE based approach has poor quality of output distribution.

Hyunjik kim et al., 2019, arXiv Keyword: Bayesian, Process Problem: Underfitting of Neural Process Solution: NP + Self-Attention, Cross-Attention Benefits: Improvement of prediction accuracy, training speed, model capability.

Marta Garnelo et al., 2018, arXiv Keyword: Bayesian, Process Problem: Data inefficiency, hard to train multiple datasets in one.

Marta Garnelo et al., 2018, arXiv Keyword: Bayesian, Process Problem: Weakness of knowledge sharing and data inefficiency of classical supervised learning Solution: Stochastic Process + NN Benefits: Data efficient, prior sharing Contribution: Encapsulation of parameterized NN function family.