terryum/awesome-deep-learning-papers

Project overview

A curated reading list of the top 100 most cited deep learning papers published between 2012 and 2016, organized by research domain. The repository includes Python scripts to download the listed papers and gather author names, but the list is no longer maintained.

Project type

Data Processing

Use cases

Learning & Education

Deployment

Refer to project documentation

License

License pending

Best for

• Researchers and educators needing a structured reference of historical, seminal deep learning literature from 2012 to 2016.

Key capabilities

• Provides a categorized list of the top 100 deep learning papers published from 2012 to 2016.
• Includes Python scripts to download all listed top-100 papers and collect all author names, along with a bib file.

Limitations and risks

• The list is no longer maintained due to the high daily volume of new deep learning papers published since 2017.

Getting started

• The repository does not provide documented setup difficulty levels, environment requirements, or structured first-success paths for users.

Evidence and sources

• README: [Notice] This list is not being maintained anymore because of the overwhelming amount of deep learning papers published every day since 2017.
• README: A curated list of the most cited deep learning papers (2012-2016)
• README: Please note that we prefer seminal deep learning papers that can be applied to various researches rather than application papers.
• README: (Update) You can download all top-100 papers with [this](https://github.com/terryum/awesome-deep-learning-papers/blob/master/fetch_papers.py) and collect all authors' names with […

Reviewed at: 2026-07-17T11:05:46Z