Methods › Computer Vision › Likelihood-Based Generative Models › RealNVP

RealNVP

19 papers tagged archive 2025-07-28

Introduced by Laurent Dinh et al. in Density estimation using Real NVP

archive 2025-07-28 Description, source and code snippet are the archive's method entry.

RealNVP is a generative model that utilises real-valued non-volume preserving (real NVP) transformations for density estimation. The model can perform efficient and exact inference, sampling and log-density estimation of data points.

PaperSourceSee Code · chrischute/real-nvp

Papers archive 2025-07-28

19 shown of 19, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.

Tasks archive 2025-07-28

20 shown of 25 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.

TaskPapers
Anomaly Detection5
BIG-bench Machine Learning2
Defect Detection2
Time Series2
Adversarial Robustness1
Cyber Attack Detection1
Decoder1
Deep Learning1
Density Estimation1
Dimensionality Reduction1
Disentanglement1
Image Classification1
Image Generation1
Knowledge Distillation1
Language Modeling1
Language Modelling1
Object Detection1
Prognosis1
Representation Learning1
Sign Language Recognition1

Usage over time archive 2025-07-28

Papers per year tagged with RealNVP: 2016 to 2024, peak 5 5 0 2016: 1 paper 2016 2017: 0 papers 2017 2018: 0 papers 2018 2019: 4 papers 2019 2020: 5 papers 2020 2021: 3 papers 2021 2022: 1 paper 2022 2023: 1 paper 2023 2024: 4 papers 2024
Papers per year the archive tags with this method, by the paper's archive date (19 dated). Bars are counts, not a trend claim.

Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).

Categories archive 2025-07-28

Likelihood-Based Generative ModelsGenerative Models

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