Diana21170648's Stars
coder2gwy/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。
HypothesisWorks/hypothesis
Hypothesis is a powerful, flexible, and easy to use library for property-based testing.
gravieinc/gravie-developer-test
Gravie Software Development Engineer Test
vinta/awesome-python
An opinionated list of awesome Python frameworks, libraries, software and resources.
atinfo/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
yueyingqingfeng/Test-Development-Engineer
abhidas0810/TEST_4_DevelopmentEngineer
saikumarbt/resume
Resume of Software Development Engineer in Test (SDET)
yandex/CMICOT
Efficient feature selection method based on Conditional Mutual Information.
omesner/knncmi
This python code estimates conditional mutual information (CMI) and mutual information (MI) for discrete and/or continuous variables using a nearest neighbors approach.
sudiptodip15/CCMI
Classifier based mutual information, conditional mutual information estimation; conditional independence testing
jankova/GraphicaLasso-inference
Inference for high-dimensional graphical models using graphical Lasso and neighbourhood selection.
aangt321/Graphical-Lasso-to-Identify-Trading-Pairs-in-International-Stock-ETFs
Graphical Lasso to Identify Trading Pairs in International Stock ETFs
Niangmohamed/Probabilistic-Graphical-Lasso
Graphical Model: Probabilistic Graphical Lasso.
seanmcrae/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
dongeric/time-varying-graphical-lasso-impl
Implementation of time-varying graphical lasso from research paper (2019)
ruteee/DataBaseTennessee
A database for tennessee plant.
abi/screenshot-to-code
Drop in a screenshot and convert it to clean code (HTML/Tailwind/React/Vue)
camaramm/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).
Diana21170648/Matlab_EvidenceTheory
3(DS, Yager, sunquan) + 4(Generic framework, Average_Murphy, modifiedAverage_Deng, pignistic)
a-ghose/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.
machinelearningzuu/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
GasanaElysee12/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.
lipinski/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.
divyanshchoubisa/Learning-Graph-Neural-Networks
Some Notebooks To Start Learning GNN
abhilash1910/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.
dobraczka/GNNTutorial
A small tutorial notebook on Graph Neural Networks, especially Graph Convolutional Networks
ENCCS/gnn_transformers_notebooks
Notebooks for the ENCCS Graph Neural Networks and Transformers workshop
mohan696matlab/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.
shenweichen/GraphNeuralNetwork
Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.