Awesome-Examples of how to write a good paper for an AI open-source project
A curated, but incomplete, list of excellent writing samples on open-source AI project.
If you want to contribute to this list, please feel free to send a pull request. Also you can contact [email protected].
To whom it may be useful?
This repository gathers some awesome writing examples for the researchers and engineers who want to write a demo or industry track paper for their open-source AI projects, including but not limited to, ML/DL framework, Explainable AI(XAI), AutoML, Reinforcement Learning(RL). The resources are categorized into ML/DL engine, XAI, AutoML and RL these four types and taged into two types: Algorithm & Framework, or Platform & System.
Engine part consists of some main stream computational frameworks for machine learning and deep learning applications. We didn't include the framework without a paper e.g. Keras, PyTorch though they are very excellent libraries, because this repo mainly focuses on the writing and literacy of an open-source library and project.
Caffe ๐
Caffe: Convolutional Architecture for Fast Feature Embedding [paper] [code].
Tensorflow ๐
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems [paper] [code].
MXNet ๐
MXNet: A Flexible and Efficient Machine Learning Library for Heterogeneous Distributed Systems[paper] [code].
Theano ๐
Theano: A Python framework for fast computation of mathematical expressions[paper] [code].
Scikit-learn ๐
Scikit-learn: Machine Learning in Python[paper] [code].
XGBoost ๐
XGBoost: A Scalable Tree Boosting System[paper] [code].
LightGBM ๐
LightGBM: A Highly Efficient Gradient Boosting Decision Tree[paper] [code].
Ray ๐
Ray: A Distributed Framework for Emerging AI Applications[paper] [code].
mlpack ๐
mlpack3: A fast, flexible machine learning library[paper] [code].
AutoML
AutoML part consists of famous and active automated machine learning and neural architecture search open-source project.
Auto-Keras ๐ป
Auto-Keras: An Efficient Neural Architecture Search System[paper] [code].
Auto-WEKA ๐ป
Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms[paper] [code].
Auto-WEKA 2.0 ๐ป
Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA[paper] [code].
Auto-Sklearn ๐ป
Efficient and Robust Automated Machine Learning[paper] [code].
Auto-PyTorch ๐ป
Efficient and Robust Automated Machine Learning[paper] [code].
Tune ๐ป
Tune: A Research Platform for Distributed Model Selection and Training[paper] [code].
BOHB ๐
BOHB: Robust and Efficient Hyperparameter Optimization at Scale[paper] [code].
XAI
XAI part consists of famous and active explainable AI tools, algorithm and platform.
secml ๐ป
secml: A Python Library for Secure and Explainable Machine Learning[paper] [code].
RL
RL part consists of famous and active reinforcement learning(RL) algorithm tools, platform and system.
TorchBeast ๐ป
TorchBeast: A PyTorch Platform for Distributed RL [paper] [code].
RLlib ๐ป
RLlib: Abstractions for Distributed Reinforcement Learning [paper] [code].
RLcard ๐ป
RLCard: A Toolkit for Reinforcement Learning in Card Games [paper] [code].
Tensorlayer ๐ป
TensorLayer: A Versatile Library for Efficient Deep Learning Development [paper] [code].