zhouqiaor

zhouqiaor's Stars

• convexfi/spectralGraphTopology

  Structured Graph Learning via Laplacian Spectral Constraints (NeurIPS 2019)

  Language:R5917

• epfl-lts2/gspbox

  Graph Signal Processing in Matlab

  Language:MATLAB13757

• epfl-lts2/pygsp

  Graph Signal Processing in Python

  Language:Python49094

• rodrigo-pena/graph-learning

  Language:Jupyter Notebook146

• lucfra/LDS-GNN

  Learning Discrete Structures for Graph Neural Networks (TensorFlow implementation)

  Language:Python19240

• STAC-USC/Graph_Learning

  Graph Learning from Data

  Language:MATLAB3419

• MarcSkovMadsen/awesome-streamlit

  The purpose of this project is to share knowledge on how awesome Streamlit is and can be

  Language:HTML2.1k359

• GitbookIO/gitbook

  The open source frontend for GitBook doc sites

  Language:TypeScript27.3k3.9k

• EthicalML/awesome-production-machine-learning

  A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning

  17.7k2.3k

• Jcharis/Machine-Learning-Web-Apps

  Building and Embedding Machine Learning Model into a Web App(With Flask,Streamlit,etc)

  Language:Jupyter Notebook569571

• rlan/notebooks

  A docker-based starter kit for machine learning via jupyter notebooks. Designed for those who just want a runtime environment and get on with machine learning. Docker Hub:

  Language:Dockerfile326

• lucfra/FAR-HO

  Gradient based hyperparameter optimization & meta-learning package for TensorFlow

  Language:Jupyter Notebook18847

• HobbitLong/CMC

  [arXiv 2019] "Contrastive Multiview Coding", also contains implementations for MoCo and InstDis

  Language:Python1.3k180

• zhirongw/lemniscate.pytorch

  Unsupervised Feature Learning via Non-parametric Instance Discrimination

  Language:Python751135

• yuanxiaosc/Machine-Learning-Book

  《机器学习宝典》包含：谷歌机器学习速成课程（招式）+机器学习术语表（口诀）+机器学习规则（心得）+机器学习中的常识性问题 （内功）。该资源适用于机器学习、深度学习研究人员和爱好者参考！

  Language:Jupyter Notebook1.1k266

• vermaMachineLearning/FGSD

  Graph Feature Representation/Vector Based On The Family Of Graph Spectral Distances (NIPS 2017).

  Language:Python248

• spotify/annoy

  Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

  Language:C++13.3k1.2k

• beringresearch/ivis

  Dimensionality reduction in very large datasets using Siamese Networks

  Language:Python33243

• lrjconan/GRAN

  Efficient Graph Generation with Graph Recurrent Attention Networks, Deep Generative Model of Graphs, Graph Neural Networks, NeurIPS 2019

  Language:C++47297

• benedekrozemberczki/awesome-graph-classification

  A collection of important graph embedding, classification and representation learning papers with implementations.

  Language:Python4.8k742

• jayaram-r/KNN-anomaly-detection

  K-nearest neighbors graph-based anomaly detection method

  Language:Jupyter Notebook3

• pinyuchen/FINGER

  Demo codes for fast von Neumann graph entropy computation method published at ICML 2019

  Language:MATLAB76

• xgfs/NetLSD

  NetLSD descriptors for graphs. Compare and analyze graph structure on multiple levels!

  Language:Python603

• mmasana/OoD_Mining

  Implementation of "Metric Learning for Novelty and Anomaly Detection", BMVC 2018

  Language:Python376

• pauldoust/Anomaly-Detection

  Anomaly Detection approaches using Metric Learning and Autoencoders

  Language:Jupyter Notebook1

• datamllab/pyodds

  An End-to-end Outlier Detection System

  Language:Python25239

• cs231n/cs231n.github.io

  Public facing notes page

  Language:Jupyter Notebook10.2k4.1k

• ZhouYuxuanYX/Unsupervised-Deep-Learning-Framework-for-Anomaly-Detection-in-Time-Series-

  Unsupervised deep learning framework with online(MLP: prediction-based, 1 D Conv and VAE: reconstruction-based, Wavenet: prediction-based) settings for anaomaly detection in time series data

  Language:Python11934

• albertcthomas/anomaly_detection_lab

  Introduction to unsupervised anomaly detection

  Language:Jupyter Notebook610

• WangXuhongCN/OCGNN

  my implement of my paper

  Language:Python6320