Survey of Likelihood-based Generative Models Keyword: VAE, Normalizing Flows, Neural ODE, Energy-based Models, Diffusion Models, Score Models, Schrodinger Bridge, Rectified Flows, Flow Models, Consistency Models, Flow Map Models, Distribution Matching Distillation, Drifting Models Abstract

SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows, Nielsen et al.

Invertible Residual Networks, Behrmann et al. In ICML 2019, arXiv.

ANF, Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models, Huang et al.

Glow: Generative Flow with Invertible 1x1 Convolutions, Kingma and Dhariwal, 2018, arXiv Flow++: Improving Flow-Based Generative Models with Variational Dequantization and Architecture Design, Jonathan Ho et al.

Variational Inference with Normalizing Flows, Rezende and Mohamed, 2015, arXiv Density Estimation using Real NVP, Dinh et al.