About awesome-deep-learning-papers
The most cited deep learning papers
What you should know about awesome-deep-learning-papers
awesome-deep-learning-papers — The most cited deep learning papers. It is categorized under AI Tools . The project has gathered 26,121 stars and 4,437 forks on GitHub, indicating strong adoption among developers.
Pricing & licensing: This tool is offered free of charge , released under the Unknown license. The source code is openly available on GitHub, allowing engineers to audit, contribute, or fork as needed.
Use cases & topics: awesome-deep-learning-papers is associated with the following topics: deep-learning, deep-neural-networks, machine-learning. Teams working in deep-learning / deep-neural-networks / machine-learning spaces typically evaluate this kind of tool when scoping new architecture decisions or replacing legacy components.
Getting started: Check out the official GitHub repository for installation steps, configuration examples, and the latest release notes. Most teams hit value within the first week if the tool aligns with their existing AI Tools stack.
Editor's note from Fanny Engriana (Founder, Wardigi Digital Agency): when evaluating tools in the AI Tools category for our agency clients, we look at three things first — license clarity, community size, and active maintenance. Tools with explicit license terms and ongoing commits tend to remain viable across multi-year projects.