science4fun's repositories
apollo-client
:rocket: A fully-featured, production ready caching GraphQL client for every UI framework and GraphQL server
awesome-AI-books
Some awesome AI related books and pdfs for learning and downloading
cudf
cuDF - GPU DataFrame Library
cugraph
cuGraph - RAPIDS Graph Analytics Library
deeplearning-models
A collection of various deep learning architectures, models, and tips
edge-connect
EdgeConnect: Structure Guided Image Inpainting using Edge Prediction, ICCVW 2019 https://arxiv.org/abs/1901.00212
elkai
Python 3 TSP solver based on LKH (cross platform)
faiss
A library for efficient similarity search and clustering of dense vectors.
feeling-responsive
»Feeling Responsive« is a free flexible theme for Jekyll built on Foundation framework. You can use it for your company site, as a portfolio or as a blog.
gpss19
Gaussian Process and Uncertainty Quantification Summer School 2019
graspy
Python package for graph statistics
GSTools
GeoStatTools: Geostatistical tools like random field generation, variogram estimation and covariance models.
impersonator
PyTorch implementation of our ICCV 2019 paper: Liquid Warping GAN: A Unified Framework for Human Motion Imitation, Appearance Transfer and Novel View Synthesis
lapack
LAPACK development repository
leeml-notes
李宏毅《机器学习》笔记,在线阅读地址:https://datawhalechina.github.io/leeml-notes
machine-learning-systems-design
A booklet on machine learning systems design with exercises
mml-book.github.io
Companion webpage to the book "Mathematics For Machine Learning"
PHATE
PHATE (Potential of Heat-diffusion for Affinity-based Transition Embedding) is a tool for visualizing high dimensional data.
pycma
Python implementation of CMA-ES
pygna
A python package for gene network analysis
pyinterpolate
Bunch of spatial interpolation scripts written in numpy and Python
pyod
A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)
rlpyt
Reinforcement Learning in PyTorch
tips
Most commonly used git tips and tricks.
treon
Easy to use test framework for Jupyter Notebooks
virtual_libraries
Supporting code for the paper «Generative molecular design in low data regimes»