mlsanityData to 13 Oct 2026

Normalizing Flows: An Introduction and Review of Current Methods

arXiv 1908.09257 ↗First posted 25 Aug 2019stat.ML cs.LGcited by 16

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Abstract (arXiv)

Normalizing Flows are generative models which produce tractable distributions where both sampling and density evaluation can be efficient and exact. The goal of this survey article is to give a coherent and comprehensive review of the literature around the construction and use of Normalizing Flows for distribution learning. We aim to provide context and explanation of the models, review current state-of-the-art literature, and identify open questions and promising future directions.

Key facts. Cited by 16 papers in the map (data through 13 Oct 2026). First posted on arXiv 25 Aug 2019.

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Citing papers per year: 2021: 8; 2022: 2; 2023: 4; 2024: 2.

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  1. 2023IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturingcited by 64
  2. 2024Implicit Diffusion: Efficient Optimization through Stochastic Samplingcited by 22
  3. 2023Counterfactual (Non-)identifiability of Learned Structural Causal Modelscited by 17
  4. 2021Continuous Latent Process Flowscited by 10
  5. 2021Model-Based Machine Learning for Communicationscited by 8
  6. 2024Transformer Neural Autoregressive Flowscited by 7
  7. 2021Robust Classification using Hidden Markov Models and Mixtures of Normalizing Flowscited by 4
  8. 2021Normalizing Flow based Hidden Markov Models for Classification of Speech Phones with Explainabilitycited by 4
  9. 2023Probabilistic and Semantic Descriptions of Image Manifolds and Their Applicationscited by 3
  10. 2021In-game Residential Home Planning via Visual Context-aware Global Relation Learningcited by 2
  11. 2021Generative Actor-Critic: An Off-policy Algorithm Using the Push-forward Modelcited by 2
  12. 2022Modeling Time-Series and Spatial Data for Recommendations and Other Applicationscited by 2
4 more
  1. 2023PACER: A Fully Push-forward-based Distributional Reinforcement Learning Algorithmcited by 2
  2. 2021Learning and Generalization in Overparameterized Normalizing Flowscited by 1
  3. 2021Efficient spatio-temporal weather forecasting using U-Netcited by 1
  4. 2022Learning Robust Representations Of Generative Models Using Set-Based Artificial Fingerprintscited by 0