2116 Repositories
Python graph-convolutional-network Libraries
Face Detection and Alignment using Multi-task Cascaded Convolutional Networks (MTCNN)
Face-Detection-with-MTCNN Face detection is a computer vision problem that involves finding faces in photos. It is a trivial problem for humans to sol
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach
Digital Twin Mobility Profiling: A Spatio-Temporal Graph Learning Approach This is the implementation of traffic prediction code in DTMP based on PyTo
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification
Pytorch Implementation of Adversarial Deep Network Embedding for Cross-Network Node Classification (ACDNE) This is a pytorch implementation of the Adv
Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo.
stock-graph-python Simple GUI python app to show a stocks graph performance. Made with Matplotlib and Tiingo. Tiingo API Key You will need to add your
Pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021).
Pytorch code for SS-Net This is a pytorch implementation of Straight Sampling Network For Point Cloud Learning (ICIP2021). Environment Code is tested
PoC code for stealing the WiFi password of a network with a Lovebox IOT device connected
LoveBoxer PoC code for stealing the WiFi password of a network with a Lovebox IOT device connected. This PoC was is what I used in this blogpost Usage
Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric
Fast and Easy-to-use Distributed Graph Learning for PyTorch Geometric
A command line tool to create a graph representing your Ansible playbook tasks and roles
Ansible Playbook Grapher ansible-playbook-grapher is a command line tool to create a graph representing your Ansible playbook plays, tasks and roles.
Simple P2P application for sending files over open and forwarded network ports.
FileShareV2 A major overhaul to the V1 (now deprecated) FileShare application. V2 brings major improvements in both UI and performance. V2 is now base
Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering
Graph Regularized Residual Subspace Clustering Network for hyperspectral image clustering
Tool to get the top 100 of the fastest nodes in the Tor network. Based on Kirzahk tool.
Tor Network Top 100 IPs Tool to get the top 100 of the fastest nodes in the Tor network. Based on Kirzahk tool. Just execute top100ipstor.py to get th
Heterogeneous Temporal Graph Neural Network
Heterogeneous Temporal Graph Neural Network This repository contains the datasets and source code of HTGNN. run_mag.ipynb is the training and testing
Code for "Learning Graph Cellular Automata"
Learning Graph Cellular Automata This code implements the experiments from the NeurIPS 2021 paper: "Learning Graph Cellular Automata" Daniele Grattaro
Open source single image super-resolution toolbox containing various functionality for training a diverse number of state-of-the-art super-resolution models. Also acts as the companion code for the IEEE signal processing letters paper titled 'Improving Super-Resolution Performance using Meta-Attention Layers’.
Deep-FIR Codebase - Super Resolution Meta Attention Networks About This repository contains the main coding framework accompanying our work on meta-at
BMVC 2021 Oral: code for BI-GCN: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation
BMVC 2021 BI-GConv: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation Necassary Dependencies: PyTorch 1.2.0 Python 3.
VACA: Designing Variational Graph Autoencoders for Interventional and Counterfactual Queries
VACA Code repository for the paper "VACA: Designing Variational Graph Autoencoders for Interventional and Counterfactual Queries (arXiv)". The impleme
Rot-Pro: Modeling Transitivity by Projection in Knowledge Graph Embedding
Rot-Pro : Modeling Transitivity by Projection in Knowledge Graph Embedding This repository contains the source code for the Rot-Pro model, presented a
Node Dependent Local Smoothing for Scalable Graph Learning
Node Dependent Local Smoothing for Scalable Graph Learning Requirements Environments: Xeon Gold 5120 (CPU), 384GB(RAM), TITAN RTX (GPU), Ubuntu 16.04
Code for approximate graph reduction techniques for cardinality-based DSFM, from paper
SparseCard Code for approximate graph reduction techniques for cardinality-based DSFM, from paper "Approximate Decomposable Submodular Function Minimi
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs
SMORE: Knowledge Graph Completion and Multi-hop Reasoning in Massive Knowledge Graphs SMORE is a a versatile framework that scales multi-hop query emb
OneFlow is a performance-centered and open-source deep learning framework.
OneFlow OneFlow is a performance-centered and open-source deep learning framework. Latest News Version 0.5.0 is out! First class support for eager exe
Hierarchical User Intent Graph Network for Multimedia Recommendation
Hierarchical User Intent Graph Network for Multimedia Recommendation This is our Pytorch implementation for the paper: Hierarchical User Intent Graph
Dist2Dec: A Simplicial Neural Network for Homology Localization
Dist2Dec: A Simplicial Neural Network for Homology Localization
Video Matting via Consistency-Regularized Graph Neural Networks
Video Matting via Consistency-Regularized Graph Neural Networks Project Page | Real Data | Paper Installation Our code has been tested on Python 3.7,
The code repository for "RCNet: Reverse Feature Pyramid and Cross-scale Shift Network for Object Detection" (ACM MM'21)
RCNet: Reverse Feature Pyramid and Cross-scale Shift Network for Object Detection (ACM MM'21) By Zhuofan Zong, Qianggang Cao, Biao Leng Introduction F
Covid-19 Test AI (Deep Learning - NNs) Software. Accuracy is the %96.5, loss is the 0.09 :)
Covid-19 Test AI (Deep Learning - NNs) Software I developed a segmentation algorithm to understand whether Covid-19 Test Photos are positive or negati
Unofficial pytorch implementation of the paper "Context Reasoning Attention Network for Image Super-Resolution (ICCV 2021)"
CRAN Unofficial pytorch implementation of the paper "Context Reasoning Attention Network for Image Super-Resolution (ICCV 2021)" This code doesn't exa
Research on controller area network Intrusion Detection Systems
Group members information Member 1: Lixue Liang Member 2: Yuet Lee Chan Member 3: Xinruo Zhang Member 4: Yifei Han User Manual Generate Attack Packets
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training
Predicting lncRNA–protein interactions based on graph autoencoders and collaborative training Code for our paper "Predicting lncRNA–protein interactio
Pytorch implementation of Cut-Thumbnail in the paper Cut-Thumbnail:A Novel Data Augmentation for Convolutional Neural Network.
Cut-Thumbnail (Accepted at ACM MULTIMEDIA 2021) Tianshu Xie, Xuan Cheng, Xiaomin Wang, Minghui Liu, Jiali Deng, Tao Zhou, Ming Liu This is the officia
Unofficial implement with paper SpeakerGAN: Speaker identification with conditional generative adversarial network
Introduction This repository is about paper SpeakerGAN , and is unofficially implemented by Mingming Huang ([email protected]), Tiezheng Wang (wtz920729
Space Time Recurrent Memory Network - Pytorch
Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio
A quick and dirty script to scan the network, find default credentials on services and post a message to a Slack channel with the results.
A quick and dirty script to scan the network, find default credentials on services and post a message to a Slack channel with the results.
Sharing of contents on mitochondrial encounter networks
mito-network-sharing Sharing of contents on mitochondrial encounter networks Required: R with igraph, brainGraph, ggplot2, and XML libraries; igraph l
Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance
Nested Graph Neural Networks About Nested Graph Neural Network (NGNN) is a general framework to improve a base GNN's expressive power and performance.
Exponential Graph is Provably Efficient for Decentralized Deep Training
Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C
The source codes for TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation.
TME The source codes for TME-BNA: Temporal Motif-Preserving Network Embedding with Bicomponent Neighbor Aggregation. Our implementation is based on TG
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"
Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie
Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021).
AA-RMVSNet Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021) in PyTorch. paper link: arXiv | CVF Change Log Ju
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).
NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti
Python3 program to control Elgato Ring Light on your local network without Elgato's Control Center software
Elgato Light Controller I'm really happy with my Elgato Key Light from an illumination perspective. However, their control software has been glitchy f
Light-weight network, depth estimation, knowledge distillation, real-time depth estimation, auxiliary data.
light-weight-depth-estimation Boosting Light-Weight Depth Estimation Via Knowledge Distillation, https://arxiv.org/abs/2105.06143 Junjie Hu, Chenyou F
The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining Concept-Oriented Shared Information".
The HIST framework for stock trend forecasting The implementation of the paper "HIST: A Graph-based Framework for Stock Trend Forecasting via Mining C
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
A PyTorch Implementation of Gated Graph Sequence Neural Networks (GGNN)
A PyTorch Implementation of GGNN This is a PyTorch implementation of the Gated Graph Sequence Neural Networks (GGNN) as described in the paper Gated G
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson
Multi-layer convolutional LSTM with Pytorch
Convolution_LSTM_pytorch Thanks for your attention. I haven't got time to maintain this repo for a long time. I recommend this repo which provides an
BMN: Boundary-Matching Network
BMN: Boundary-Matching Network A pytorch-version implementation codes of paper: "BMN: Boundary-Matching Network for Temporal Action Proposal Generatio
Simple python script for automated network scans with random name generator(useful for CTF boxes).
📄 Automated NMAP script Description Simple python script for automated network scans with random name generator(useful for CTF boxes). Requirements 1
Count the frequency of letters or words in a text file and show a graph.
Word Counter By EBUS Coding Club Count the frequency of letters or words in a text file and show a graph. Requirements Python 3.9 or higher matplotlib
A script that trains a model to recognize handwritten digits using the MNIST data set.
handwritten-digits-recognition A script that trains a model to recognize handwritten digits using the MNIST data set. Then it loads external files and
Official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Imbalance Classification"
DPGNN This repository is an official PyTorch(Geometric) implementation of DPGNN(DPGCN) in "Distance-wise Prototypical Graph Neural Network for Node Im
ConformalLayers: A non-linear sequential neural network with associative layers
ConformalLayers: A non-linear sequential neural network with associative layers ConformalLayers is a conformal embedding of sequential layers of Convo
Dynamic Graph Event Detection
DyGED Dynamic Graph Event Detection Get Started pip install -r requirements.txt TODO Paper link to arxiv, and how to cite. Twitter Weather dataset tra
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud
Harmonic Memory Networks for Graph Completion
HMemNetworks Code and documentation for Harmonic Memory Networks, a series of models for compositionally assembling representations of graph elements
A Broader Picture of Random-walk Based Graph Embedding
Random-walk Embedding Framework This repository is a reference implementation of the random-walk embedding framework as described in the paper: A Broa
CvT-ASSD: Convolutional vision-Transformerbased Attentive Single Shot MultiBox Detector (ICTAI 2021 CCF-C 会议)The 33rd IEEE International Conference on Tools with Artificial Intelligence
CvT-ASSD including extra CvT, CvT-SSD, VGG-ASSD models original-code-website: https://github.com/albert-jin/CvT-SSD new-code-website: https://github.c
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC
arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro
A novel pipeline framework for multi-hop complex KGQA task. About the paper title: Improving Multi-hop Embedded Knowledge Graph Question Answering by Introducing Relational Chain Reasoning
Rce-KGQA A novel pipeline framework for multi-hop complex KGQA task. This framework mainly contains two modules, answering_filtering_module and relati
Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
GCN_LogsigRNN This repository holds the codebase for the paper: Logsig-RNN: a novel network for robust and efficient skeleton-based action recognition
Wanli Li and Tieyun Qian: Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction, IJCNN 2021
MRefG Wanli Li and Tieyun Qian: "Exploit a Multi-head Reference Graph for Semi-supervised Relation Extraction", IJCNN 2021 1. Requirements To reproduc
CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary.
CUP-DNN CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary. The model was trained on the expre
CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhancement
CBREN This is the Pytorch implementation for our IEEE TCSVT paper : CBREN: Convolutional Neural Networks for Constant Bit Rate Video Quality Enhanceme
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021)
MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021) Overview We release the code of the MVFNet (Multi-View Fusion Network).
Visualize the electric field of a point charge network.
ElectriPy ⚡ Visualize the electric field of a point charges network. 🔌 Installation Install ElectriPy package: $ pip install electripy You are all d
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"
MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori
Graveyard is an attempt at open-source reimplementation of DraciDoupe.cz
Graveyard: Place for Dead (and Undead) Graveyard is an attempt at open-source reimplementation of DraciDoupe.cz (referred to as DDCZ in this text). De
Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch
Enformer - Pytorch (wip) Implementation of Enformer, Deepmind's attention network for predicting gene expression, in Pytorch. The original tensorflow
Convolutional neural network web app trained to track our infant’s sleep schedule using our Google Nest camera.
Machine Learning Sleep Schedule Tracker What is it? Convolutional neural network web app trained to track our infant’s sleep schedule using our Google
Neo4j Movies Example application with Flask backend using the neo4j-python-driver
Neo4j Movies Application: Quick Start This example application demonstrates how easy it is to get started with Neo4j in Python. It is a very simple we
This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021.
MCGC Description This is the code of "Multi-view Contrastive Graph Clustering" in NeurlPS 2021. Datasets Results ACM DBLP IMDB Amazon photos Amazon co
PyTorch implementation of Convolutional Neural Fabrics http://arxiv.org/abs/1606.02492
PyTorch implementation of Convolutional Neural Fabrics arxiv:1606.02492 There are some minor differences: The raw image is first convolved, to obtain
Very Deep Convolutional Networks for Large-Scale Image Recognition
pytorch-vgg Some scripts to convert the VGG-16 and VGG-19 models [1] from Caffe to PyTorch. The converted models can be used with the PyTorch model zo
Convolutional Recurrent Neural Network (CRNN) for image-based sequence recognition.
Convolutional Recurrent Neural Network This software implements the Convolutional Recurrent Neural Network (CRNN), a combination of CNN, RNN and CTC l
Convolutional Neural Network for 3D meshes in PyTorch
MeshCNN in PyTorch SIGGRAPH 2019 [Paper] [Project Page] MeshCNN is a general-purpose deep neural network for 3D triangular meshes, which can be used f
A Pytorch implementation of "LegoNet: Efficient Convolutional Neural Networks with Lego Filters" (ICML 2019).
LegoNet This code is the implementation of ICML2019 paper LegoNet: Efficient Convolutional Neural Networks with Lego Filters Run python train.py You c
Django database backed celery periodic task scheduler with support for task dependency graph
Djag Scheduler (Dj)ango Task D(AG) (Scheduler) Overview Djag scheduler associates scheduling information with celery tasks The task schedule is persis
Spatial-Temporal Transformer for Dynamic Scene Graph Generation, ICCV2021
Spatial-Temporal Transformer for Dynamic Scene Graph Generation Pytorch Implementation of our paper Spatial-Temporal Transformer for Dynamic Scene Gra
Official Code Release for Container : Context Aggregation Network
Container: Context Aggregation Network Official Code Release for Container : Context Aggregation Network Comparion between CNN, MLP-Mixer and Transfor
Adaptive, interpretable wavelets across domains (NeurIPS 2021)
Adaptive wavelets Wavelets which adapt given data (and optionally a pre-trained model). This yields models which are faster, more compressible, and mo
Self-supervised learning on Graph Representation Learning (node-level task)
graph_SSL Self-supervised learning on Graph Representation Learning (node-level task) How to run the code To run GRACE, sh run_GRACE.sh To run GCA, sh
A lightweight library to compare different PyTorch implementations of the same network architecture.
TorchBug is a lightweight library designed to compare two PyTorch implementations of the same network architecture. It allows you to count, and compar
Apply our monocular depth boosting to your own network!
MergeNet - Boost Your Own Depth Boost custom or edited monocular depth maps using MergeNet Input Original result After manual editing of base You can
Key information extraction from invoice document with Graph Convolution Network
Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro
A banking system is a group or network of institutions that provide financial services for us
A banking system is a group or network of institutions that provide financial services for us. These institutions are responsible for operating a payment system, providing loans, taking deposits, and helping with investments.
Mini SCADA. Poll modbus devices by TCP/IP network.
Plans Add saving and loading devices and channels with files or db or someone else. Multitasking system for poll all devices Automatic optimization po
External Network Pentest Automation using Shodan API and other tools.
Chopin External Network Pentest Automation using Shodan API and other tools. Workflow Input a file containing CIDR ranges. Converts CIDR ranges to ind
Facilitates implementing deep neural-network backbones, data augmentations
Introduction Nowadays, the training of Deep Learning models is fragmented and unified. When AI engineers face up with one specific task, the common wa
CoSMA: Convolutional Semi-Regular Mesh Autoencoder. From Paper "Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes"
Mesh Convolutional Autoencoder for Semi-Regular Meshes of Different Sizes Implementation of CoSMA: Convolutional Semi-Regular Mesh Autoencoder arXiv p
A lightweight Python-based 3D network multi-agent simulator. Uses a cell-based congestion model. Calculates risk, loudness and battery capacities of the agents. Suitable for 3D network optimization tasks.
AMAZ3DSim AMAZ3DSim is a lightweight python-based 3D network multi-agent simulator. It uses a cell-based congestion model. It calculates risk, battery
Meta graph convolutional neural network-assisted resilient swarm communications
Resilient UAV Swarm Communications with Graph Convolutional Neural Network This repository contains the source codes of Resilient UAV Swarm Communicat
An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition
CRNN paper:An End-to-End Trainable Neural Network for Image-based Sequence Recognition and Its Application to Scene Text Recognition 1. create your ow
The ibet-Prime security token management system for ibet network.
ibet-Prime The ibet-Prime security token management system for ibet network. Features ibet-Prime is an API service that enables the issuance and manag
Network Enhancement implementation in pytorch
network_enahncement_pytorch Network Enhancement implementation in pytorch Research paper Network Enhancement: a general method to denoise weighted bio