terryum/awesome-deep-learning-papers
The most cited deep learning papers
From the publisher
README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
[](https://github.com/sindresorhus/awesome) [Notice] This list is not being maintained anymore because of the overwhelming amount of deep learning papers published every day since 2017. A curated list of the most cited deep learning papers (2012-2016) We believe that there exist classic deep learning papers which are worth reading regardless of their application domain. Rather than providing overwhelming amount of papers, We would like to provide a curated list of the awesome deep learning papers which are considered as must-reads in certain research domains. Before this list, there exist other awesome deep learning lists, for example, Deep Vision and Awesome Recurrent Neural Networks. Also, after this list comes out, another awesome list for deep learning beginners, called Deep Learning Papers Reading Roadmap, has been created and loved by many deep learning researchers. Although the Roadmap List includes lots of important deep learning papers, it feels overwhelming for me to read them all.…
Read the full README ↗ · Preview checked 2026-11-01T16:00:11.854Z
Inside the original README — Document outline
- Awesome - Most Cited Deep Learning Papers
- Background
- Awesome list criteria
- Contents
- Understanding / Generalization / Transfer
- Optimization / Training Techniques
- Unsupervised / Generative Models
- Convolutional Neural Network Models
- Image: Segmentation / Object Detection
- Image / Video / Etc
- Natural Language Processing / RNNs
- Speech / Other Domain
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Links from the README
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What this repository does
The most cited deep learning papers
Repository facts
- Owner
- terryum
- Primary language
- TeX
- Stars
- 26,200
- Forks
- 4,397
- Open issues + pull requests
- 38
- License
- Not reported — inspect the license file
- Archived
- No
- Default branch
- master
- Created
- 2016-06-03T06:48:30.000Z
- Last push
- 2024-01-18T13:29:44.000Z
Topics and intended use
Owner-supplied topics: deep-learning, deep-neural-networks, machine-learning
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Source and freshness
Source: GitHub. Metadata observed 2026-11-01T12:19:42.808Z. Daily imports are snapshots, not real-time monitoring.
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