must-read-ai-papers
A collection of must-read AI-related papers (by minhlong94)
paper_annotations
A place to keep track of all the annotated papers. (by au1206)
| must-read-ai-papers | paper_annotations | |
|---|---|---|
| 1 | 11 | |
| 13 | 137 | |
| - | - | |
| 0.0 | 0.0 | |
| about 2 years ago | over 1 year ago | |
| MIT License | MIT License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
must-read-ai-papers
Posts with mentions or reviews of must-read-ai-papers.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-03-15.
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What is the top paper that one must absolutely read in their deep learning roadmap?
I have a short list of papers here that I really enjoy reading, ranging a lot of topics, not just DL. Hope it can serve as a reference. https://github.com/minhlong94/must-read-ai-papers
paper_annotations
Posts with mentions or reviews of paper_annotations.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-09-03.
- Wood Trim Problem (Help Needed)
- Beginning to read ML papers - pathway/general advice
- What is the top paper that one must absolutely read in their deep learning roadmap?
- Keeping up
- How to read more research papers? (tips & tools given)
- Does anyone know a good source for learning the basics of ML? (beginner)
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Annotated Papers: RoBERTa and Few Shot NER
These along with other papers can be found at: https://github.com/au1206/paper_annotations and https://au1206.github.io/
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Annotated Papers: The EfficientNet Family (v1 and v2)
Read along with these easy to follow annotated papers: EfficientNet-V1: https://au1206.github.io/annotated%20paper/EfficientNet/ EfficientNet-V2: https://au1206.github.io/annotated%20paper/EfficientNet-v2/ Github Repo: https://github.com/au1206/paper_annotations
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Fine-Tune BERT for Text Classification with TensorFlow Tutorial
I will also often post annotated papers, where I will try to annotate a recent paper and try to make it more readable for a better understanding for the people just starting out. You can find some at https://au1206.github.io/ and will now consciously try to make it easier to understand.
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Annotated Paper: MLP-Mixer An all MLP Architecture for Vision
Paper Complexity: Easy-Medium Annotated paper link: https://au1206.github.io/annotated%20paper/mlp_mixer/ Github Link: https://github.com/au1206/paper_annotations/blob/master/mlp_mixer.pdf
What are some alternatives?
When comparing must-read-ai-papers and paper_annotations you can also consider the following projects:
awesome-artificial-intelligence-research - A curated list of Artificial Intelligence (AI) Research, tracks the cutting edge trending of AI research, including recommender systems, computer vision, machine learning, etc.
awesome-deep-learning-papers - The most cited deep learning papers
awesome-artificial-intelligence - A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
ml-surveys - 📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
cs-video-courses - List of Computer Science courses with video lectures.