Share an application platform that provides machine learning papers, code, datasets, and evaluation tools, Papers with Code。
Features include:
- Paper and code links: Users can find related open-source code by searching for papers, connecting academic research with practical applications.
- Datasets and evaluation tables: The platform provides benchmark datasets and evaluation tables for various tasks, making it easy to compare algorithm performance and results.
- Community contributions and editing: Anyone can submit code implementations, add tasks, or evaluation results through the edit button, promoting knowledge sharing.
Competition result sharing: Competition organizers can mirror competition results to the platform for easy display and tracking.
It seems very interesting (it could be a better way to waste time in group meetings), and like kaggle, it is a valuable learning resource for newcomers like me.
I found that I had actually clicked on this website while searching for InfoNCE and contrastive learning, but I only realized how many features this site has when I received a push from the video platform. It seems that clicking on the about section or checking the homepage while browsing search results is a good habit; you might find surprises.