Methods › General › Regularization › Dropout

Dropout

27,472 papers tagged archive 2025-07-28

Introduced by Nitish Srivastava et al. in Dropout: A Simple Way to Prevent Neural Networks from Overfitting

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

Dropout is a regularization technique for neural networks that drops a unit (along with connections) at training time with a specified probability p (a common value is p=0.5). At test time, all units are present, but with weights scaled by p (i.e. w becomes pw).

The idea is to prevent co-adaptation, where the neural network becomes too reliant on particular connections, as this could be symptomatic of overfitting. Intuitively, dropout can be thought of as creating an implicit ensemble of neural networks.

PaperSourceSee Code · google/jax

Papers archive 2025-07-28

30 shown of 27,472, 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 2,664 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
Language Modelling3,032
Language Modeling2,374
Retrieval1,822
Question Answering1,494
Decoder1,416
Sentence1,364
RAG1,363
Retrieval-augmented Generation1,181
Translation1,106
Image Classification1,001
Machine Translation953
Transfer Learning874
Semantic Segmentation871
Large Language Model838
image-classification791
Classification784
Text Generation767
Object Detection743
object-detection662
Representation Learning661

Usage over time archive 2025-07-28

Papers per year tagged with Dropout: 2014 to 2025, peak 7,070 7,070 0 2014: 24 papers 2014 2015: 78 papers 2015 2016: 121 papers 2016 2017: 211 papers 2017 2018: 469 papers 2018 2019: 1480 papers 2019 2020: 2645 papers 2020 2021: 3617 papers 2021 2022: 3539 papers 2022 2023: 5366 papers 2023 2024: 7070 papers 2024 2025: 2852 papers 2025
Papers per year the archive tags with this method, by the paper's archive date (27,472 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

Regularization

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