Python Graph-domain-adaptation Resources

SGPA: Structure-Guided Prior Adaptation for Category-Level 6D Object Pose Estimation This is the PyTorch implemention of ICCV'21 paper SGPA: Structure

A python3 script for search possible misconfiguration in a DNS related to security protections of email service from the domain name. This project is for educational use, we are not responsible for its misuse.

GPU implementation of kNN and SNN GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors Supported by numba cuda and faiss library E

TensorDebugger (TDB) is a visual debugger for deep learning. It extends TensorFlow (Google's Deep Learning framework) with breakpoints + real-time visualization of the data flowing through the computational graph.

ECLARE ECLARE: Extreme Classification with Label Graph Correlations @InProceedings{Mittal21b, author = "Mittal, A. and Sachdeva, N. and Agrawal

GalaXC GalaXC: Graph Neural Networks with Labelwise Attention for Extreme Classification @InProceedings{Saini21, author = {Saini, D. and Jain,

Meta Self-Learning for Multi-Source Domain Adaptation: A Benchmark Project | Arxiv | YouTube | | Abstract In recent years, deep learning-based methods

Separation of Mainlobes and Sidelobes in the Ultrasound Image Based on the Spatial Covariance (MIST) and Aperture-Domain Spectrum of Received Signals

必要なソフト・パッケージ Python3 Numpy JSON Matplotlib 動作確認環境 MacBook Air M1 Python 3.8.2 (arm64) Numpy 1.22.0 Matplotlib 3.5.1 JSON 2.0.9 使い方 draw_time_histgram(

TCNN Pandey A, Wang D L. TCNN: Temporal convolutional neural network for real-time speech enhancement in the time domain[C]//ICASSP 2019-2019 IEEE Int

List of disposable email domains This repo contains a list of disposable and temporary email address domains often used to register dummy users in ord

GraphMLTutorialNLDL22 Tutorial NLDL22: Introduction to Graph Machine Learning, with Jupyter notebooks This tutorial takes place during the conference

LibMTL LibMTL is an open-source library built on PyTorch for Multi-Task Learning (MTL). See the latest documentation for detailed introductions and AP

Scene Graph Generation from Natural Language Supervision This repository includes the Pytorch code for our paper "Learning to Generate Scene Graph fro

MSDorkDump is a Google Dork File Finder that queries a specified domain name and variety of file extensions (pdf, doc, docx, etc), and downloads them.

Pytorch Implementation of Learning Mesh-based Simulation With Graph Networks This is the unofficial implementation of the approach described in the pa

Minimalistic tool to visualize how the routes to a given target domain change over time, feat. Python 3.10 & mermaid.js

Node-level Graph Regression with Deep Gaussian Process Models Prerequests our implementation is mainly based on tensorflow 1.x and gpflow 1.x: python

FairEdit Relevent Publication FairEdit: Preserving Fairness in Graph Neural Networks through Greedy Graph Editing

TBSG: Tree-based Search Graph for Approximate Nearest Neighbor Search. TBSG is a graph-based algorithm for ANNS based on Cover Tree, which is also an

DeepKE is a knowledge extraction toolkit supporting low-resource and document-level scenarios for entity, relation and attribute extraction. We provide comprehensive documents, Google Colab tutorials, and online demo for beginners.

1 MAGNN This repo is the official implementation for Multi-Scale Adaptive Graph Neural Network for Multivariate Time Series Forecasting. 1.1 The frame

VisionKG: Vision Knowledge Graph Official Repository of VisionKG by Anh Le-Tuan, Trung-Kien Tran, Manh Nguyen-Duc, Jicheng Yuan, Manfred Hauswirth and

PPGNet: Learning Point-Pair Graph for Line Segment Detection PyTorch implementation of our CVPR 2019 paper: PPGNet: Learning Point-Pair Graph for Line

Dynamic Stock Industrial Classification Use graph-based analysis to re-classify stocks and experiment different re-classification methodologies to imp

Code for "An Empirical Investigation of Domian Generalization with Empirical Risk Minimizers" (NeurIPS 2021) Motivation and Introduction Domain Genera

Dagon - An Asynchronous Task Graph Execution Engine Dagon is a job execution sys

Simple implementation of Equivariant GNN A short implementation of E(n) Equivariant Graph Neural Networks for HOMO energy prediction. Just 50 lines of

This is the course project of AI3602: Data Mining of SJTU. Group Members include Jinghao Feng, Mingyang Jiang and Wenzhong Zheng.

Table of Contents Introduction Installation Examples Pre-trained models Quick start using colab JARVIS-ALIGNN webapp Peformances on a few datasets Use

Graph-to-3D This is the official implementation of the paper Graph-to-3d: End-to-End Generation and Manipulation of 3D Scenes Using Scene Graphs | arx

LQVAE-separation Code for "Unsupervised Source Separation via Bayesian inference in the latent domain" Paper Samples GT Compressed Separated Drums GT

ReceptiveFieldAnalysisToolbox This is RFA-Toolbox, a simple and easy-to-use library that allows you to optimize your neural network architectures usin

Graph-based CTR prediction This is a repository designed for graph-based CTR prediction methods, it includes our graph-based CTR prediction methods: F

Security audit Python project dependencies against security advisory databases.

PYGON A Graph Neural Network Tool for Recovering Dense Sub-graphs in Random Dense Graphs. Installation This code requires to install and run the graph

Decompose to Adapt: Cross-domain Object Detection via Feature Disentanglement In this project, we proposed a Domain Disentanglement Faster-RCNN (DDF)

tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener

Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In

1 Meta-FDMIxup Repository for the paper : Meta-FDMixup: Cross-Domain Few-Shot Learning Guided byLabeled Target Data. (ACM MM 2021) paper News! the rep

GraphFPN: Graph Feature Pyramid Network for Object Detection Download graph-FPN-main.zip For training , run: python train.py For test with Graph_fpn

FlatGCN This is the official Pytorch-version code of FlatGCN (Flattened Graph Convolutional Networks for Recommendation, submitted to ICASSP2022). Req

This application aims to read all wifi passwords and visualizes the complexity in graph formation by taking into account several criteria and help you generate new random passwords.

Python + Poetry REST API with FastAPI, hosted on GCP This template will get you ready to deploy a FastAPI app in Google Cloud with automatic API versi

GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et

Dual Path Learning for Domain Adaptation of Semantic Segmentation Official PyTorch implementation of "Dual Path Learning for Domain Adaptation of Sema

Domain Adaptive Video Segmentation via Temporal Consistency Regularization Updates 08/2021: check out our domain adaptation for sematic segmentation p

Robustness via Cross-Domain Ensembles [ICCV 2021, Oral] This repository contains tools for training and evaluating: Pretrained models Demo code Traini

Skeletal-GNN Code for "Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation" ICCV'21 Various deep learning techniques have been propose

Spatio-Temporal Dynamic Inference Network for Group Activity Recognition The source codes for ICCV2021 Paper: Spatio-Temporal Dynamic Inference Networ

Scene Graph Generation Object Detections Ground truth Scene Graph Generated Scene Graph In this visualization, woman sitting on rock is a zero-shot tr

Multi-Anchor Active Domain Adaptation for Semantic Segmentation Munan Ning*, Donghuan Lu*, Dong Wei†, Cheng Bian, Chenglang Yuan, Shuang Yu, Kai Ma, Y

Documentation | Paper [JMLR] | Tutorials | Benchmarks | Examples DIG: Dive into Graphs is a turnkey library for graph deep learning research. Why DIG?

Introduction This is a crawler I wrote in Python using the APIs of Telethon months ago. This tool was not intended to be publicly available for a numb

d o t m o t i f Find graph motifs using intuitive notation DotMotif is a library that identifies subgraphs or motifs in a large graph. It looks like t

Whois-Python-GUI Get Whois Domain with Python - GUI :) WARNING Dont Copy ! - W

Heroku Cloudflare App Domain Creating branded herokuapp.com-like domains using Cloudflare, based on the app name (eg my-app-prod.example.com). Feature

CSAC Introduction This repository contains the implementation code for paper: Co

Multi-level Disentanglement Graph Neural Network (MD-GNN) This is a PyTorch implementation of the MD-GNN, and the code includes the following modules:

✔️ Linux ✔️ OS X ❌ Windows (#39) Welcome to graph-app-kit Turn your graph data into a secure and interactive visual graph app in 15 minutes! Why This

TechSEO Crawler Build a small, 3 domain internet using Github pages and Wikipedia and construct a crawler to crawl, render, and index. Play with the r

KIND (Kessler Italian Named-entities Dataset) KIND is an Italian dataset for Named-Entity Recognition. It contains more than one million tokens with t

mask-uncertainty-in-HSI This repository contains the testing code and pre-trained models for the paper Calibrated Hyperspectral Image Reconstruction v

Fast-Partial-Ranking-MNL This repo provides a PyTorch implementation for the CopulaGNN models as described in the following paper: Fast Learning of MN

OptDom: Learning Optimal Representations for Domain Generalization This repository contains the official implementation for Optimal Representations fo

cluster-link-prediction This repository provides some of the code implemented and the data used for the work proposed in "A Cluster-Based Trip Predict

MDFEND: Multi-domain Fake News Detection This is an official implementation for MDFEND: Multi-domain Fake News Detection which has been accepted by CI

Deep Transfer Learning on PyTorch This is a PyTorch library for deep transfer learning. We divide the code into two aspects: Single-source Unsupervise

CoCosNet Pytorch Implementation of the paper "Cross-domain Correspondence Learning for Exemplar-based Image Translation" (CVPR 2020 oral). Update: 202

MT-GAN-PyTorch PyTorch Implementation of AAAI-2020 Paper "Learning to Transfer: Unsupervised Domain Translation via Meta-Learning" Dependency: Python

Better Cross-Domain Feature Disentanglement and Manipulation with Improved PuppetGAN Quite cool... Right? Introduction This repo contains a TensorFlow

DosGAN-PyTorch PyTorch Implementation of Exploring Explicit Domain Supervision for Latent Space Disentanglement in Unpaired Image-to-Image Translation

Multi-Domain Multi-Modality I2I translation Pytorch implementation of multi-modality I2I translation for multi-domains. The project is an extension to

AsymmetricGAN for Image-to-Image Translation AsymmetricGAN Framework for Multi-Domain Image-to-Image Translation AsymmetricGAN Framework for Hand Gest

AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti

Domain Transfer Network (DTN) TensorFlow implementation of Unsupervised Cross-Domain Image Generation. Requirements Python 2.7 TensorFlow 0.12 Pickle

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

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

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

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 ?

Inlets Colab Run CodeServer on Colab using Inlets in less than 60 secs using your own domain. Features Optimized for Inlets/InletsPro Use your own Cus

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

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