paper_annotations
best_AI_papers_2021
| paper_annotations | best_AI_papers_2021 | |
|---|---|---|
| 11 | 30 | |
| 137 | 2,912 | |
| - | - | |
| 0.0 | 2.7 | |
| over 1 year ago | 8 months ago | |
| MIT License | MIT License |
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.
paper_annotations
- 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
best_AI_papers_2021
- The past two years went down in a blink because of some pandemic? Check out this 2021 recap of the most exciting advancements in the AI field to see what you may have missed out on!
- GitHub - louisfb01/best_AI_papers_2021: A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
What are some alternatives?
awesome-deep-learning-papers - The most cited deep learning papers
aws-mlu-explain - Visual, Interactive Articles About Machine Learning: https://mlu-explain.github.io/
must-read-ai-papers - A collection of must-read AI-related papers
CVPR2024-Papers-with-Code - CVPR 2024 论文和开源项目合集
Best_AI_paper_2020 - A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code
license-against-the-machine - Strictly no AIs
rtdl - Research on Tabular Deep Learning (Python package & papers) [Moved to: https://github.com/Yura52/rtdl]
best_AI_papers_2022 - A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.
sandlib
AltStore-Beginners-Guide - An un-official guide to installing AltStore.
morphogenesis-resources - Resources on the topic of digital morphogenesis (creating form with code). Includes links to major articles, code repos, creative projects, books, software, and more.
AlgoWiki - Repository which contains links and resources on different topics of Computer Science.