Diana21170648's starred repositories

awesome-python

An opinionated list of awesome Python frameworks, libraries, software and resources.

Language:PythonLicense:NOASSERTIONStargazers:219852Issues:6036Issues:0

screenshot-to-code

Drop in a screenshot and convert it to clean code (HTML/Tailwind/React/Vue)

Language:PythonLicense:MITStargazers:56328Issues:327Issues:296

coder2gwy

互联网首份程序员考公指南,由3位已经进入体制内的前大厂程序员联合献上。

hypothesis

Hypothesis is a powerful, flexible, and easy to use library for property-based testing.

Language:PythonLicense:NOASSERTIONStargazers:7522Issues:72Issues:1587

awesome-test-automation

A curated list of awesome test automation frameworks, tools, libraries, and software for different programming languages. Sponsored by https://zapple.tech and https://automated-testing.info

GraphNeuralNetwork

Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.

Language:PythonLicense:MITStargazers:782Issues:12Issues:7

tennessee-eastman-profBraatz

The Fortran 77 codes for the open-loop and the closed-loop simulations for the Tennessee Eastman process (TEP) as well as the training and testing data files used for evaluating the data-driven methods (PCA, PLS, FDA, and CVA).

Language:FortranLicense:NOASSERTIONStargazers:124Issues:6Issues:6

CMICOT

Efficient feature selection method based on Conditional Mutual Information.

Language:C++License:NOASSERTIONStargazers:42Issues:14Issues:0

CCMI

Classifier based mutual information, conditional mutual information estimation; conditional independence testing

knncmi

This python code estimates conditional mutual information (CMI) and mutual information (MI) for discrete and/or continuous variables using a nearest neighbors approach.

Language:PythonLicense:GPL-3.0Stargazers:31Issues:2Issues:0

Deep-Graph-Learning

A notebook containing implementations of different graph deep node embeddings along with benchmark graph neural network models in tensorflow. This has been taken from https://www.kaggle.com/abhilash1910/nlp-workshop-ml-india-deep-graph-learning to apply GNNs/node embeddings on NLP task.

Language:Jupyter NotebookStargazers:13Issues:2Issues:0

GNNTutorial

A small tutorial notebook on Graph Neural Networks, especially Graph Convolutional Networks

Language:Jupyter NotebookLicense:MITStargazers:12Issues:3Issues:0

gnn_transformers_notebooks

Notebooks for the ENCCS Graph Neural Networks and Transformers workshop

Language:Jupyter NotebookStargazers:11Issues:5Issues:0

BG-CNN-for-DC-Motor-FDI

BG-CNN: A Hybrid Fault Diagnosis Method for Improved Fault Isolation. This repository presents the BG-CNN method, a novel approach that combines the Bond-Graph technique with Convolutional Neural Networks (CNNs) for efficient fault isolation.

Language:Jupyter NotebookLicense:MITStargazers:7Issues:1Issues:0

Learning-Graph-Neural-Networks

Some Notebooks To Start Learning GNN

Language:Jupyter NotebookStargazers:6Issues:1Issues:0

time-varying-graphical-lasso-impl

Implementation of time-varying graphical lasso from research paper (2019)

Language:Jupyter NotebookStargazers:4Issues:1Issues:0

graph-neural-network

The repository is a collection of Jupyter notebooks showcasing various projects related to graph neural networks (GNNs). Each notebook provides a detailed explanation of the project and its implementation, making it easy for users to understand and replicate the results.

Language:Jupyter NotebookStargazers:4Issues:2Issues:0

DataBaseTennessee

A database for tennessee plant.

Language:CStargazers:4Issues:3Issues:0

GraphicalLasso-GaussianMixture

Lasso + Gaussian Mixture Models With this kernel I want to demonstrate how to use Gaussian mixture Models (GMM) which have the nice property to train unsupervised, so you can also use the test set. I use Graphical Lasso as an estimator for the initial value of precision matrix (= inverse Covariance) and mean

Language:Jupyter NotebookLicense:Apache-2.0Stargazers:4Issues:0Issues:0

GCN_Notebooks

This repo contains notebooks pertaining to Graph Convolutional Neural Networks and their application on brain imaging data to predict stages of Alzheimer's disease. This research was conducted in Brookhaven National Laboratory's HSRP program. All datasets have been removed.

Language:Jupyter NotebookStargazers:3Issues:0Issues:0

GraphicaLasso-inference

Inference for high-dimensional graphical models using graphical Lasso and neighbourhood selection.

Language:RStargazers:3Issues:0Issues:0

Probabilistic-Graphical-Lasso

Graphical Model: Probabilistic Graphical Lasso.

Language:HTMLLicense:MITStargazers:3Issues:2Issues:0

Graphical-Lasso-to-Identify-Trading-Pairs-in-International-Stock-ETFs

Graphical Lasso to Identify Trading Pairs in International Stock ETFs

Language:Jupyter NotebookStargazers:2Issues:1Issues:0

Graph-Neural-Network

In this notebook we are going to show how you can convert tabular data into graph and use it to do your task using graph neural network.

Language:Jupyter NotebookStargazers:2Issues:0Issues:0

gravie-developer-test

Gravie Software Development Engineer Test

Matlab_EvidenceTheory

3(DS, Yager, sunquan) + 4(Generic framework, Average_Murphy, modifiedAverage_Deng, pignistic)

Language:PythonStargazers:1Issues:0Issues:0

pytorch-notebooks

In this repository I'm implementing PyTorch based Deep Neural Networks from basic ANN to Advanced Graph Neural Networks. Please suggest if you have any ideas

Language:Jupyter NotebookStargazers:1Issues:2Issues:0

resume

Resume of Software Development Engineer in Test (SDET)

License:MITStargazers:1Issues:0Issues:0
Language:PythonStargazers:1Issues:0Issues:0