Methods › Computer Vision › Generative Models › RAE

Regularized Autoencoders

RAE

26 papers tagged archive 2025-07-28

Introduced by Partha Ghosh et al. in From Variational to Deterministic Autoencoders

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

This method introduces several regularization schemes that can be applied to an Autoencoder. To make the model generative ex-post density estimation is proposed and consists in fitting a Mixture of Gaussian distribution on the train data embeddings after the model is trained.

PaperSourceSee Code · clementchadebec/benchmark_VAE

Papers archive 2025-07-28

26 shown of 26, 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 41 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
Decoder3
Dimensionality Reduction2
Adversarial Attack1
Adversarial Robustness1
Anomaly Detection1
Attribute1
Autonomous Driving1
Clustering1
Decision Making1
Denoising1
Density Estimation1
Descriptive1
EEG1
Electroencephalogram (EEG)1
Hallucination1
Image Generation1
Image Restoration1
In-Context Learning1
Language Modeling1
Language Modelling1

Usage over time archive 2025-07-28

Papers per year tagged with RAE: 2019 to 2025, peak 7 7 0 2019: 3 papers 2019 2020: 7 papers 2020 2021: 2 papers 2021 2022: 4 papers 2022 2023: 3 papers 2023 2024: 3 papers 2024 2025: 4 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (26 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

Generative Models

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