A curated reading list of the 100 most cited deep learning papers published between 2012 and 2016, organized to help researchers and educators survey foundational research. It includes Python scripts for downloading the listed papers, but the collection is no longer maintained.
Project overview
Provides a focused starting point for navigating foundational deep learning literature, specifically targeting seminal works over application-specific papers.
Project type
Data Processing · Learning Resources
Use cases
Learning & Education
Deployment
Refer to project documentation
License
License pending
Best for
Researchers and educators looking for a categorized reading guide to the seminal deep learning papers published between 2012 and 2016.
Key capabilities
Provides a catalog of the top 100 deep learning papers published from 2012 to 2016, sorted and grouped by research domain.
Includes Python scripts designed to download all top-100 papers and extract all author names. The repository also provides a bib file for citations.
Limitations and risks
The list is no longer updated due to the high daily volume of new deep learning publications since 2017. It does not reflect research developments after 2016.
Getting started
Setup and installation instructions are not documented. Users should expect to configure their own environment to run the provided Python scripts for paper downloads.
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 […