best_AI_papers_2022
exploring-AI-optimization
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| best_AI_papers_2022 | exploring-AI-optimization | |
|---|---|---|
| 21 | 22 | |
| 3,201 | 109 | |
| - | 3.7% | |
| 3.6 | 3.8 | |
| 6 months ago | 7 months ago | |
| MIT License | MIT License |
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best_AI_papers_2022
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What are the most important papers on AI that you would recommend?
Nonetheless, here's something I vaguely recall glancing over (a collection of one person's opinion on the most significant papers of 2022). https://github.com/louisfb01/best_AI_papers_2022
- [R][P] 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.
- A curated list of the latest breakthroughs in AI in 2022 with video demo, article, and code [work in progress]
exploring-AI-optimization
- Collection of material on optimizing deep learning models
- Collection of material on optimization techniques for neural networks
- Collection of resources on quantization
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[P] Open source that takes as input a deep learning model and outputs a version that runs faster in inference. Now faster and easier to use (New release)
[1] Quantization. Techniques and Concept Map. [2] Pruning. Techniques and Concept Map. [3] ONNX Runtime [4] Nvidia TensorRT [5] Intel OpenVINO [6] Apache TVM
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Accelerating AI models online discussion
https://github.com/nebuly-ai/learning-AI-optimization/blob/main/Pruning.md here you have open source collection of material on the topic :)
- What is pruning a neural network? A guide on github. Feedback is welcome!
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[P] Concept maps and research material on artificial intelligence optimization techniques (pruning and quantization). A guide on GitHub
Quantization github maps
What are some alternatives?
Proton-Crypter - Proton Crypter can be used fo education penetration test, personal tests, and to protect legal files which you do not want to be debugged or reverse engineered. We are not responsible for what you use our protection/encryption/obfuscation software for!
nebuly - The user analytics platform for LLMs
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.
awesome-ai - A curated list of artificial intelligence resources (Courses, Tools, App, Open Source Project)
top-10-cv-papers-2021 - A curated list of the top 10 computer vision papers in 2021 with video demos, articles, code and paper reference.
prunnable-layers-pytorch - Prunable nn layers for pytorch.
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
Data-science-best-resources - Carefully curated resource links for data science in one place
AltStore-Beginners-Guide - An un-official guide to installing AltStore.
tvm - Open deep learning compiler stack for cpu, gpu and specialized accelerators
Awesome-Image-Colorization - :books: A collection of Deep Learning based Image Colorization and Video Colorization papers.
CMU-ECE-CS-Guide - How to survive CMU as an ECE/CS major