mlsanityData to 14 Oct 2026

Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models

arXiv 2002.07101 ↗First posted 17 Feb 2020cs.LG stat.MLcited by 66

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Abstract (arXiv)

In this work, we propose a new family of generative flows on an augmented data space, with an aim to improve expressivity without drastically increasing the computational cost of sampling and evaluation of a lower bound on the likelihood. Theoretically, we prove the proposed flow can approximate a Hamiltonian ODE as a universal transport map. Empirically, we demonstrate state-of-the-art performance on standard benchmarks of flow-based generative modeling.

Key facts. Cited by 66 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Feb 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 20; 2022: 12; 2023: 17; 2024: 9; 2025: 4; 2026: 4.

66 papers.

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  1. 2021Score-based Generative Modeling in Latent Spacecited by 636
  2. 2021Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Modelscited by 252
  3. 2021Score-Based Generative Modeling with Critically-Damped Langevin Diffusioncited by 233
  4. 2021Likelihood Training of Schr"odinger Bridge using Forward-Backward SDEs Theorycited by 219
  5. 2023Two for One: Diffusion Models and Force Fields for Coarse-Grained Molecular Dynamicscited by 72
  6. 2023Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamicscited by 66
  7. 2021Densely connected normalizing flowscited by 49
  8. 2024Deep Generative Models through the Lens of the Manifold Hypothesis: A Survey and New Connectionscited by 47
  9. 2022CANF-VC: Conditional Augmented Normalizing Flows for Video Compressioncited by 46
  10. 2023Learning Interpolations between Boltzmann Densitiescited by 43
  11. 2021Resampling Base Distributions of Normalizing Flowscited by 42
  12. 2023SE(3) Equivariant Augmented Coupling Flowscited by 37
38 more
  1. 2022Flow-matching -- efficient coarse-graining of molecular dynamics without forcescited by 36
  2. 2023Where to Diffuse, How to Diffuse, and How to Get Back: Automated Learning for Multivariate Diffusionscited by 29
  3. 2021Implicit Normalizing Flowscited by 28
  4. 2024A Survey of Geometric Graph Neural Networks: Data Structures, Models and Applicationscited by 28
  5. 2023Rigid Body Flows for Sampling Molecular Crystal Structurescited by 27
  6. 2022Efficient-VDVAE: Less is morecited by 26
  7. 2023Free-form Flows: Make Any Architecture a Normalizing Flowcited by 26
  8. 2023Advances in machine-learning-based sampling motivated by lattice quantum chromodynamicscited by 23
  9. 2021ANFIC: Image Compression Using Augmented Normalizing Flowscited by 20
  10. 2022B-CANF: Adaptive B-frame Coding with Conditional Augmented Normalizing Flowscited by 18
  11. 2023A Review of Change of Variable Formulas for Generative Modelingcited by 13
  12. 2021Density estimation on low-dimensional manifolds: an inflation-deflation approachcited by 11
  13. 2022Semi-Discrete Normalizing Flows through Differentiable Tessellationcited by 11
  14. 2023Spatial Attention Kinetic Networks with E(n)-Equivariancecited by 11
  15. 2025Scalable Boltzmann Generators for equilibrium sampling of large-scale materialscited by 11
  16. 2021Latent Space Refinement for Deep Generative Modelscited by 10
  17. 2021Automatic variational inference with cascading flowscited by 9
  18. 2023Designing losses for data-free training of normalizing flows on Boltzmann distributionscited by 9
  19. 2024Universal Functional Regression with Neural Operator Flowscited by 9
  20. 2025VFP: Variational Flow-Matching Policy for Multi-Modal Robot Manipulationcited by 9
  21. 2021Jacobian Determinant of Normalizing Flowscited by 8
  22. 2021Universal Approximation for Log-concave Distributions using Well-conditioned Normalizing Flowscited by 7
  23. 2023Normalizing flow sampling with Langevin dynamics in the latent spacecited by 7
  24. 2022Invertible Monotone Operators for Normalizing Flowscited by 6
  25. 2022Whitening Convergence Rate of Coupling-based Normalizing Flowscited by 6
  26. 2024Stable Training of Normalizing Flows for High-dimensional Variational Inferencecited by 6
  27. 2021Spatial Dependency Networks: Neural Layers for Improved Generative Image Modelingcited by 5
  28. 2022Flowification: Everything is a Normalizing Flowcited by 5
  29. 2022Distilling Style from Image Pairs for Global Forward and Inverse Tone Mappingcited by 5
  30. 2023ELSA -- Enhanced latent spaces for improved collider simulationscited by 5
  31. 2024Fast and Unified Path Gradient Estimators for Normalizing Flowscited by 5
  32. 2024Entropy-Informed Weighting Channel Normalizing Flow for Deep Generative Modelscited by 5
  33. 2021Multi-Resolution Continuous Normalizing Flowscited by 4
  34. 2021Funnels: Exact maximum likelihood with dimensionality reductioncited by 4
  35. 2022Deterministic training of generative autoencoders using invertible layerscited by 4
  36. 2024A Non-negative VAE:the Generalized Gamma Belief Networkcited by 4
  37. 2025Fine-tuning Flow Matching Generative Models with Intermediate Feedbackcited by 4
  38. 2024TRADE: Transfer of Distributions between External Conditions with Normalizing Flowscited by 3

50 most cited of 66 All 66 (JSON)