paper_annotations
A place to keep track of all the annotated papers. (by au1206)
Annotated-ML-Papers
Annotations of the interesting ML papers I read (by shreyansh26)
| paper_annotations | Annotated-ML-Papers | |
|---|---|---|
| 11 | 1 | |
| 137 | 189 | |
| - | - | |
| 0.0 | 6.6 | |
| over 1 year ago | 12 days 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.
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)
-
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
Annotated-ML-Papers
Posts with mentions or reviews of Annotated-ML-Papers.
We have used some of these posts to build our list of alternatives
and similar projects.
-
ELMo (Deep contextualized word representations) - Annotated Paper + Paper Summary
Annotated Paper - https://github.com/shreyansh26/Annotated-ML-Papers/blob/main/ELMo.pdf
What are some alternatives?
When comparing paper_annotations and Annotated-ML-Papers you can also consider the following projects:
awesome-deep-learning-papers - The most cited deep learning papers
rust-bert - Rust native ready-to-use NLP pipelines and transformer-based models (BERT, DistilBERT, GPT2,...)
must-read-ai-papers - A collection of must-read AI-related papers
KoGPT - GPT-2 pretrained on Korean datasets.