Python Graph-convolutional-network Resources

NICE-GAN-pytorch - Official PyTorch implementation of NICE-GAN: Reusing Discriminators for Encoding: Towards Unsupervised Image-to-Image Translation

GANILLA We provide PyTorch implementation for: GANILLA: Generative Adversarial Networks for Image to Illustration Translation. Paper Arxiv Updates (Fe

DeepSIM: Image Shape Manipulation from a Single Augmented Training Sample (ICCV 2021 Oral) Project | Paper Official PyTorch implementation of the pape

We proposed an unsupervised image-to-image translation method via pre-trained StyleGAN2 network. paper: Unsupervised Image-to-Image Translation via Pr

MatchGAN: A Self-supervised Semi-supervised Conditional Generative Adversarial Network This repository is the official implementation of MatchGAN: A S

Net2Net Code accompanying the NeurIPS 2020 oral paper Network-to-Network Translation with Conditional Invertible Neural Networks Robin Rombach*, Patri

InstaGAN: Instance-aware Image-to-Image Translation Warning: This repo contains a model which has potential ethical concerns. Remark that the task of

SMIT: Stochastic Multi-Label Image-to-image Translation This repository provides a PyTorch implementation of SMIT. SMIT can stochastically translate a

Semantic Grouping Network for Video Captioning Hobin Ryu, Sunghun Kang, Haeyong Kang, and Chang D. Yoo. AAAI 2021. [arxiv] Environment Ubuntu 16.04 CU

Fashion-Entity-Classification - Fashion-MNIST is a dataset of Zalando's article images—consisting of a training set of 60,000 examples and a test set of 10,000 examples. Each example is a 28x28 grayscale image, associated with a label from 10 classes. Zalando intends Fashion-MNIST to serve as a direct drop-in replacement for the original MNIST dataset for benchmarking machine learning algorithms. It shares the same image size and structure of training and testing splits.

micropython-wifimanager-esp8266 Simple Wifi Manager for ESP8266 using MicroPytho

autoencoder Implementation of the Reducing the Dimensionality of Data with Neural Network – G. E. Hinton and R. R. Salakhutdinov paper. Notes Aim to m

DCGAN in Tensorflow Tensorflow implementation of Deep Convolutional Generative Adversarial Networks which is a stabilize Generative Adversarial Networ

DeepRL This code implements the standard deep Q-learning and dueling network with experience replay (memory buffer) for playing simple games. DQN algo

Deep Inside Convolutional Networks This is a caffe implementation to visualize the learnt model. Part of a class project at Georgia Tech Problem State

OverFeat OverFeat is a Convolutional Network-based image classifier and feature extractor. OverFeat was trained on the ImageNet dataset and participat

C3D for pytorch This is a pytorch porting of the network presented in the paper Learning Spatiotemporal Features with 3D Convolutional Networks How to

Convolutional Two-Stream Network Fusion for Video Action Recognition

Deep Learning - Image Captioning with Convolutional and Recurrent Neural Nets ========================================================================

Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 50+ Papers across Computer Visio

Glyth Graph Revision for 0.01 A simple, yet versatile, package for graphing equations on a 2-dimensional text canvas List of contents: Brief Introduct

Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation This is the official implementation for the method described in Ch

0. Introduction This repository contains the source code for our SIGCOMM'21 paper "Network Planning with Deep Reinforcement Learning". Notes The netwo

Scene-Change-Detection - A video scene detection algorithm is designed to detect a variety of different scenes within a video. There is a very simple definition for a scene: It is a series of logically and chronologically related shots taken in a specific order to depict an over-arching concept or story.

Centauro Ferramenta de rede O Centauro é uma ferramenta de linha de comando com

BasicNeuralNetwork - This project looks over the basic structure of a neural network and how machine learning training algorithms work. For this project, I used the sigmoid function as an activation function along with stochastic gradient descent to adjust the weights and biases.

OSMnx Examples OSMnx is a Python package to work with street networks and other spatial data from OpenStreetMap: retrieve, model, analyze, and visuali

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

Augmented Traffic Control Full documentation for the project is available at http://facebook.github.io/augmented-traffic-control/. Overview Augmented

imagededup is a python package that simplifies the task of finding exact and near duplicates in an image collection.

PySOT is a software system designed by SenseTime Video Intelligence Research team. It implements state-of-the-art single object tracking algorit

Please read the blog post that goes with this code! Jupyter Notebook Setup System Requirements: Python, pip (Optional) virtualenv To start the Jupyter

GANs in Action by Jakub Langr and Vladimir Bok List of available code: Chapter 2: Colab, Notebook Chapter 3: Notebook Chapter 4: Notebook Chapter 6: C

Coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models

Speech Emotion Analyzer The idea behind creating this project was to build a machine learning model that could detect emotions from the speech we have

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

TensorFlow 101: Introduction to Deep Learning I have worked all my life in Machine Learning, and I've never seen one algorithm knock over its benchmar

Saliency Methods 🔴 Now framework-agnostic! (Example core notebook) 🔴 🔗 For further explanation of the methods and more examples of the resulting ma

Few-shot face translation A GAN based approach for one model to swap them all. The table below shows our priliminary face-swapping results requiring o

What is Detectron2-FC Detectron2-FC a fast construction platform of neural network algorithm based on detectron2. We have been working hard in two dir

Official Discussion Group (Telegram): https://t.me/video2x A Discord server is also available. Please note that most developers are only on Telegram.

CapsNet-Tensorflow A Tensorflow implementation of CapsNet based on Geoffrey Hinton's paper Dynamic Routing Between Capsules Notes: The current version

PointNet: Deep Learning on Point Sets for 3D Classification and Segmentation Created by Charles R. Qi, Hao Su, Kaichun Mo, Leonidas J. Guibas from Sta

Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi

Simple-Neural-Network From Scratch in Python This is a simple Neural Network created without any Machine Learning Libraries. The only dependencies are

Taxonomizing local versus global structure in neural network loss landscapes Int

Total number of Spanning Trees in a Graph This is a python script just written f

Description This script helps the user to show network information such as ip ad

PPL Quantization Tool(PPL 量化工具) PPL Quantization Tool (PPQ) is a powerful offlin

Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto

Neural Fractal Create Fractals Using Complex-Valued Neural Networks! Home Page Features Define Dynamical Systems Using Complex-Valued Neural Networks

Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open

EfficientFace Zengqun Zhao, Qingshan Liu, Feng Zhou. "Robust Lightweight Facial Expression Recognition Network with Label Distribution Training". AAAI

PyTorch Implementation of SSTN for Hyperspectral Image Classification Paper links: SSTN published on IEEE T-GRS. Also, you can directly find the imple

Neural Machine Translation communication system The model is basically direct to convert one source language to another targeted language using encode

DeFi wallet on Chia Network.

This repository contains source code for the experiments in a paper titled Semi-Supervised Learning with Ladder Networks by A Rasmus, H Valpola, M Hon

Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi

Weakly-Supervised Semantic Segmentation Network with Deep Seeded Region Growing (CVPR2018) By Zilong Huang, Xinggang Wang, Jiasi Wang, Wenyu Liu and J

Sequence labeler This is a neural network sequence labeling system. Given a sequence of tokens, it will learn to assign labels to each token. Can be u

Semi-supervised Adversarial Learning to Generate Photorealistic Face Images of New Identities from 3D Morphable Model Baris Gecer 1, Binod Bhattarai 1

Class-Attentive Diffusion Network for Semi-Supervised Classification Official Implementation of AAAI 2021 paper Class-Attentive Diffusion Network for

Strongly local p-norm-cut algorithms for semi-supervised learning and local graph clustering

Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne

Neural Structured Learning in TensorFlow Neural Structured Learning (NSL) is a new learning paradigm to train neural networks by leveraging structured

Graph-based joint model with Nonignorable Missingness (GNM) This is a Keras implementation of the GNM model in paper ’Graph-Based Semi-Supervised Lear

G3NN This repo provides a pytorch implementation for the 4 instantiations of the flexible generative framework as described in the following paper: A

Graph Contrastive Learning with Augmentations PyTorch implementation for Graph Contrastive Learning with Augmentations [poster] [appendix] Yuning You*

CCGL: Contrastive Cascade Graph Learning This repo provides a reference implementation of Contrastive Cascade Graph Learning (CCGL) framework as descr

GitHub Activity Generator A script that helps you instantly generate a beautiful GitHub Contributions Graph for the last year. Before 😐 😶 😒 After ?

A simplistic and efficient pure-python neural network library from Phys Whiz with CPU and GPU support.

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training Original implementation for paper GCC: Graph Contrastive Coding for Graph Neural N

GRACE The official PyTorch implementation of deep GRAph Contrastive rEpresentation learning (GRACE). For a thorough resource collection of self-superv

GMI (Graphical Mutual Information) Graph Representation Learning via Graphical Mutual Information Maximization (Peng Z, Huang W, Luo M, et al., WWW 20

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Pretraining on Dynamic Graph Neural Networks Our article is PT-DGNN and the code is modified based on GPT-GNN Requirements python 3.6 Ubuntu 18.04.5 L

DGI Deep Graph Infomax (Veličković et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom

Unsupervised Attributed Multiplex Network Embedding (DMGI) Overview Nodes in a multiplex network are connected by multiple types of relations. However

Heterogeneous-Deep-Graph-Infomax Parameter Setting: HDGI-A: Node-level dimension: 16 Attention head: 4 Semantic-level attention vector: 8 learning rat

Subg-Con Sub-graph Contrast for Scalable Self-Supervised Graph Representation Learning (Jiao et al., ICDM 2020): https://arxiv.org/abs/2009.10273 Over

Graph-InfoClust-GIC [PAKDD 2021] PAKDD'21 version Graph InfoClust: Maximizing Coarse-Grain Mutual Information in Graphs Preprint version Graph InfoClu

ncnn ncnn is a high-performance neural network inference computing framework optimized for mobile platforms. ncnn is deeply considerate about deployme

No-Transaction Band Network: A Neural Network Architecture for Efficient Deep Hedging Minimal implementation and experiments of "No-Transaction Band N

Log4jUnifi Exploiting CVE-2021-44228 in Unifi Network Application for remote cod

Numerical Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe

Lunar Lunar is a neural network aimbot that uses real-time object detection accelerated with CUDA on Nvidia GPUs. About Lunar can be modified to work

MC Outpost A Python server and client application that tracks player session times and server status About MC Outpost provides a session graph and ser

PyMeasure scientific package PyMeasure makes scientific measurements easy to set up and run. The package contains a repository of instrument classes a

Minecraft Network Pinger Minecraft Multi-Server Pinger Discord Embed What does this bot do? It sends an embed and uses mcsrvstat API and checks if the

Electrical Network Analyzer A simple electrical network analyzer. Given the oriented graph of the electrical network (circut), BASED ON computer-aided

This custom component for Home assistant adds support for Midea dehumidifier appliances via the local area network. homeassistant-midea-dehumidifier-l

模式识别大作业——人脸检测与识别平台 本项目是一个简易的人脸检测识别平台，提供了人脸信息录入和人脸识别的功能。前端采用 html+css+js，后端采用 pytorch，

Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm

SUGAR Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism" Overview train.py: the cor

BiNE: Bipartite Network Embedding This repository contains the demo code of the paper: BiNE: Bipartite Network Embedding. Ming Gao, Leihui Chen, Xiang

NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).

SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe

Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We

Pretrain-Recsys This is our Tensorflow implementation for our WSDM 2021 paper: Bowen Hao, Jing Zhang, Hongzhi Yin, Cuiping Li, Hong Chen. Pre-Training