3192 Repositories
Python graph-data-augmentation Libraries
A Red Team tool for exfiltrating sensitive data from Jira tickets.
Jir-thief This Module will connect to Jira's API using an access token, export to a word .doc, and download the Jira issues that the target has access
GraphGT: Machine Learning Datasets for Graph Generation and Transformation
GraphGT: Machine Learning Datasets for Graph Generation and Transformation Dataset Website | Paper Installation Using pip To install the core environm
Differentiable Factor Graph Optimization for Learning Smoothers @ IROS 2021
Differentiable Factor Graph Optimization for Learning Smoothers Overview Status Setup Datasets Training Evaluation Acknowledgements Overview Code rele
WRENCH: Weak supeRvision bENCHmark
🔧 What is it? Wrench is a benchmark platform containing diverse weak supervision tasks. It also provides a common and easy framework for development
Official Python wrapper for the Quantel Finance API
Quantel is a powerful financial data and insights API. It provides easy access to world-class financial information. Quantel goes beyond just financial statements, giving users valuable information like insider transactions, major shareholder transactions, share ownership, peers, and so much more.
Graph-based community clustering approach to extract protein domains from a predicted aligned error matrix
Using a predicted aligned error matrix corresponding to an AlphaFold2 model , returns a series of lists of residue indices, where each list corresponds to a set of residues clustering together into a pseudo-rigid domain.
Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown.
Evidence enables analysts to deliver a polished business intelligence system using SQL and markdown
prettymaps - A minimal Python library to draw customized maps from OpenStreetMap data.
A small set of Python functions to draw pretty maps from OpenStreetMap data. Based on osmnx, matplotlib and shapely libraries.
Auto-updating data to assist in investment to NEPSE
Symbol Ratios Summary Sector LTP Undervalued Bonus % MEGA Strong Commercial Banks 368 5 10 JBBL Strong Development Banks 568 5 10 SIFC Strong Finance
Pipeline for fast building text classification TF-IDF + LogReg baselines.
Text Classification Baseline Pipeline for fast building text classification TF-IDF + LogReg baselines. Usage Instead of writing custom code for specif
Public API client for GETTR, a "non-bias [sic] social network," designed for data archival and analysis.
GoGettr GoGettr is an API client for GETTR, a "non-bias [sic] social network." (We will not reward their domain with a hyperlink.) GoGettr is built an
[Preprint] "Bag of Tricks for Training Deeper Graph Neural Networks A Comprehensive Benchmark Study" by Tianlong Chen*, Kaixiong Zhou*, Keyu Duan, Wenqing Zheng, Peihao Wang, Xia Hu, Zhangyang Wang
Bag of Tricks for Training Deeper Graph Neural Networks: A Comprehensive Benchmark Study Codes for [Preprint] Bag of Tricks for Training Deeper Graph
Image transformations designed for Scene Text Recognition (STR) data augmentation. Published at ICCV 2021 Workshop on Interactive Labeling and Data Augmentation for Vision.
Data Augmentation for Scene Text Recognition (ICCV 2021 Workshop) (Pronounced as "strog") Paper Arxiv Why it matters? Scene Text Recognition (STR) req
Code for the KDD 2021 paper 'Filtration Curves for Graph Representation'
Filtration Curves for Graph Representation This repository provides the code from the KDD'21 paper Filtration Curves for Graph Representation. Depende
A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21
MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen
We present a framework for training multi-modal deep learning models on unlabelled video data by forcing the network to learn invariances to transformations applied to both the audio and video streams.
Multi-Modal Self-Supervision using GDT and StiCa This is an official pytorch implementation of papers: Multi-modal Self-Supervision from Generalized D
Local trajectory planner based on a multilayer graph framework for autonomous race vehicles.
Graph-Based Local Trajectory Planner The graph-based local trajectory planner is python-based and comes with open interfaces as well as debug, visuali
Generative Models as a Data Source for Multiview Representation Learning
GenRep Project Page | Paper Generative Models as a Data Source for Multiview Representation Learning Ali Jahanian, Xavier Puig, Yonglong Tian, Phillip
Import, visualize, and analyze SpiderFoot OSINT data in Neo4j, a graph database
SpiderFoot Neo4j Tools Import, visualize, and analyze SpiderFoot OSINT data in Neo4j, a graph database Step 1: Installation NOTE: This installs the sf
Low code JSON to extract data in one line
JSON Inline Low code JSON to extract data in one line ENG RU Installation pip install json-inline Usage Rules Modificator Description ?key:value Searc
A Pythonic Data Catalog powered by Ray that brings exabyte-level scalability and fast, ACID-compliant, change-data-capture to your big data workloads.
DeltaCAT DeltaCAT is a Pythonic Data Catalog powered by Ray. Its data storage model allows you to define and manage fast, scalable, ACID-compliant dat
The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"
SIGIR2021-EGLN The implement of paper "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization" Neural graph based Col
Data Preparation, Processing, and Visualization for MoVi Data
MoVi-Toolbox Data Preparation, Processing, and Visualization for MoVi Data, https://www.biomotionlab.ca/movi/ MoVi is a large multipurpose dataset of
Part-Aware Data Augmentation for 3D Object Detection in Point Cloud
Part-Aware Data Augmentation for 3D Object Detection in Point Cloud This repository contains a reference implementation of our Part-Aware Data Augment
A PyTorch implementation of the Relational Graph Convolutional Network (RGCN).
Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv
Official repository with code and data accompanying the NAACL 2021 paper "Hurdles to Progress in Long-form Question Answering" (https://arxiv.org/abs/2103.06332).
Hurdles to Progress in Long-form Question Answering This repository contains the official scripts and datasets accompanying our NAACL 2021 paper, "Hur
Parametric Contrastive Learning (ICCV2021)
Parametric-Contrastive-Learning This repository contains the implementation code for ICCV2021 paper: Parametric Contrastive Learning (https://arxiv.or
A weakly-supervised scene graph generation codebase. The implementation of our CVPR2021 paper ``Linguistic Structures as Weak Supervision for Visual Scene Graph Generation''
README.md shall be finished soon. WSSGG 0 Overview 1 Installation 1.1 Faster-RCNN 1.2 Language Parser 1.3 GloVe Embeddings 2 Settings 2.1 VG-GT-Graph
Official PyTorch implementation of the paper: Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting.
Improving Graph Neural Network Expressivity via Subgraph Isomorphism Counting Official PyTorch implementation of the paper: Improving Graph Neural Net
Nasdaq Cloud Data Service (NCDS) provides a modern and efficient method of delivery for realtime exchange data and other financial information. This repository provides an SDK for developing applications to access the NCDS.
Nasdaq Cloud Data Service (NCDS) Nasdaq Cloud Data Service (NCDS) provides a modern and efficient method of delivery for realtime exchange data and ot
Using python-binance to provide websocket data to freqtrade
The goal of this project is to provide an alternative way to get realtime data from Binance and use it in freqtrade despite the exchange used. It also uses talipp for computing
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data
Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data arXiv This is the code base for weakly supervised NER. We provide a
Script de monitoramento de telemetria para missões espaciais, cansat e foguetemodelismo.
Aeroespace_GroundStation Script de monitoramento de telemetria para missões espaciais, cansat e foguetemodelismo. Imagem 1 - Dashboard realizando moni
Home Assistant integration for spanish electrical data providers (e.g., datadis)
homeassistant-edata Esta integración para Home Assistant te permite seguir de un vistazo tus consumos y máximas potencias alcanzadas. Para ello, se ap
PyTorch implementation of spectral graph ConvNets, NIPS’16
Graph ConvNets in PyTorch October 15, 2017 Xavier Bresson http://www.ntu.edu.sg/home/xbresson https://github.com/xbresson https://twitter.com/xbresson
Graph Convolutional Networks in PyTorch
Graph Convolutional Networks in PyTorch PyTorch implementation of Graph Convolutional Networks (GCNs) for semi-supervised classification [1]. For a hi
This repository contains a streaming Dataflow pipeline written in Python with Apache Beam, reading data from PubSub.
Sample streaming Dataflow pipeline written in Python This repository contains a streaming Dataflow pipeline written in Python with Apache Beam, readin
PanGraphViewer -- show panenome graph in an easy way
PanGraphViewer -- show panenome graph in an easy way Table of Contents Versions and dependences Desktop-based panGraphViewer Library installation for
Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot. Graph Convolutional Networks for Hyperspectral Image Classification, IEEE TGRS, 2021.
Graph Convolutional Networks for Hyperspectral Image Classification Danfeng Hong, Lianru Gao, Jing Yao, Bing Zhang, Antonio Plaza, Jocelyn Chanussot T
Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks.
Heterogeneous Graph Benchmark Revisiting, benchmarking, and refining Heterogeneous Graph Neural Networks. Roadmap We organize our repo by task, and on
Natural Language Processing library built with AllenNLP 🌲🌱
Custom Natural Language Processing with big and small models 🌲🌱
Python ELT Studio, an application for building ELT (and ETL) data flows.
The Python Extract, Load, Transform Studio is an application for performing ELT (and ETL) tasks. Under the hood the application consists of a two parts.
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".
Graphormer By Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng*, Guolin Ke, Di He*, Yanming Shen and Tie-Yan Liu. This repo is the official impl
VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning
VisualGPT Our Paper VisualGPT: Data-efficient Adaptation of Pretrained Language Models for Image Captioning Main Architecture of Our VisualGPT Downloa
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery
A powerful and flexible machine learning platform for drug discovery
Test django schema and data migrations, including migrations' order and best practices.
django-test-migrations Features Allows to test django schema and data migrations Allows to test both forward and rollback migrations Allows to test th
Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.
Genalog is an open source, cross-platform python package allowing generation of synthetic document images with custom degradations and text alignment capabilities.
A light-weight image labelling tool for Python designed for creating segmentation data sets.
An image labelling tool for creating segmentation data sets, for Django and Flask.
Download history data from binance and save to dataframe or csv file
Binance history data downloader Download history data from binance and save to dataframe or csv file
Slack bot for monitoring your Metaflow flows!
Metaflowbot - Slack Bot for your Metaflow flows! Metaflowbot makes it fun and easy to monitor your Metaflow runs, past and present. Imagine starting a
Creates a C array from a hex-string or a stream of binary data.
hex2array-c Creates a C array from a hex-string. Usage Usage: python3 hex2array_c.py HEX_STRING [-h|--help] Use '-' to read the hex string from STDIN.
Collective Multi-type Entity Alignment Between Knowledge Graphs (WWW'20)
CG-MuAlign A reference implementation for "Collective Multi-type Entity Alignment Between Knowledge Graphs", published in WWW 2020. If you find our pa
Implementation of "Selection via Proxy: Efficient Data Selection for Deep Learning" from ICLR 2020.
Selection via Proxy: Efficient Data Selection for Deep Learning This repository contains a refactored implementation of "Selection via Proxy: Efficien
Defending graph neural networks against adversarial attacks (NeurIPS 2020)
GNNGuard: Defending Graph Neural Networks against Adversarial Attacks Authors: Xiang Zhang ([email protected]), Marinka Zitnik (marinka@hms.
Data from "HateCheck: Functional Tests for Hate Speech Detection Models" (Röttger et al., ACL 2021)
In this repo, you can find the data from our ACL 2021 paper "HateCheck: Functional Tests for Hate Speech Detection Models". "test_suite_cases.csv" con
SelfAugment extends MoCo to include automatic unsupervised augmentation selection.
SelfAugment extends MoCo to include automatic unsupervised augmentation selection. In addition, we've included the ability to pretrain on several new datasets and included a wandb integration.
Procedural 3D data generation pipeline for architecture
Synthetic Dataset Generator Authors: Stanislava Fedorova Alberto Tono Meher Shashwat Nigam Jiayao Zhang Amirhossein Ahmadnia Cecilia bolognesi Dominik
Amazon Scraper: A command-line tool for scraping Amazon product data
Amazon Product Scraper: 2021 Description A command-line tool for scraping Amazon product data to CSV or JSON format(s). Requirements Python 3 pip3 Ins
PyGCL: Graph Contrastive Learning Library for PyTorch
PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL components from published papers, standardized evaluation, and experiment management.
A Data Annotation Tool for Semantic Segmentation, Object Detection and Lane Line Detection.(In Development Stage)
Data-Annotation-Tool How to Run this Tool? To run this software, follow the steps: git clone https://github.com/Autonomous-Car-Project/Data-Annotation
open-information-extraction-system, build open-knowledge-graph(SPO, subject-predicate-object) by pyltp(version==3.4.0)
中文开放信息抽取系统, open-information-extraction-system, build open-knowledge-graph(SPO, subject-predicate-object) by pyltp(version==3.4.0)
Scraping Thailand COVID-19 data from the DDC's tableau dashboard
Scraping COVID-19 data from DDC Dashboard Scraping Thailand COVID-19 data from the DDC's tableau dashboard. Data is updated at 07:30 and 08:00 daily.
DenseClus is a Python module for clustering mixed type data using UMAP and HDBSCAN
DenseClus is a Python module for clustering mixed type data using UMAP and HDBSCAN. Allowing for both categorical and numerical data, DenseClus makes it possible to incorporate all features in clustering.
ml4h is a toolkit for machine learning on clinical data of all kinds including genetics, labs, imaging, clinical notes, and more
ml4h is a toolkit for machine learning on clinical data of all kinds including genetics, labs, imaging, clinical notes, and more
This repository is home to the Optimus data transformation plugins for various data processing needs.
Transformers Optimus's transformation plugins are implementations of Task and Hook interfaces that allows execution of arbitrary jobs in optimus. To i
Minimal Ethereum fee data viewer for the terminal, contained in a single python script.
Minimal Ethereum fee data viewer for the terminal, contained in a single python script. Connects to your node and displays some metrics in real-time.
This solution helps you deploy Data Lake Infrastructure on AWS using CDK Pipelines.
CDK Pipelines for Data Lake Infrastructure Deployment This solution helps you deploy data lake infrastructure on AWS using CDK Pipelines. This is base
PyGCL: Graph Contrastive Learning Library for PyTorch
PyGCL: Graph Contrastive Learning for PyTorch PyGCL is an open-source library for graph contrastive learning (GCL), which features modularized GCL com
Google Project: Search and auto-complete sentences within given input text files, manipulating data with complex data-structures.
Auto-Complete Google Project In this project there is an implementation for one feature of Google's search engines - AutoComplete. Autocomplete, or wo
This repository contains data used in the NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deployment in Text to Speech Systems
Proteno This is the data release associated with the corresponding NAACL 2021 Paper - Proteno: Text Normalization with Limited Data for Fast Deploymen
Data and Code for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning"
Introduction Code and data for ACL 2021 Paper "Inter-GPS: Interpretable Geometry Problem Solving with Formal Language and Symbolic Reasoning". We cons
OpenGAN: Open-Set Recognition via Open Data Generation
OpenGAN: Open-Set Recognition via Open Data Generation ICCV 2021 (oral) Real-world machine learning systems need to analyze novel testing data that di
Official implementation of the paper "AAVAE: Augmentation-AugmentedVariational Autoencoders"
AAVAE Official implementation of the paper "AAVAE: Augmentation-AugmentedVariational Autoencoders" Abstract Recent methods for self-supervised learnin
Code release for our paper, "SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo"
SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan
MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space
Update (20 Jan 2020): MODALS on text data is avialable MODALS MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space Table of Conte
Code for ICCV 2021 paper "Distilling Holistic Knowledge with Graph Neural Networks"
HKD Code for ICCV 2021 paper "Distilling Holistic Knowledge with Graph Neural Networks" cifia-100 result The implementation of compared methods are ba
Extract Thailand COVID-19 Cluster data from daily briefing pdf.
Thailand COVID-19 Cluster Data Extraction About Extract Clusters from Thailand Daily COVID-19 briefing PDF Download latest data Here. Data will be upd
This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust.
Demo BERT ONNX pipeline written in rust This demo showcase the use of onnxruntime-rs with a GPU on CUDA 11 to run Bert in a data pipeline with Rust. R
Evidently helps analyze machine learning models during validation or production monitoring
Evidently helps analyze machine learning models during validation or production monitoring. The tool generates interactive visual reports and JSON profiles from pandas DataFrame or csv files. Currently 6 reports are available.
Collect super-resolution related papers, data, repositories
Collect super-resolution related papers, data, repositories
Use this script to track the gains of cryptocurrencies using historical data and display it on a super-imposed chart in order to find the highest performing cryptocurrencies historically
crypto-performance-tracker Use this script to track the gains of cryptocurrencies using historical data and display it on a super-imposed chart in ord
Automated data scraper for Thailand COVID-19 data
The Researcher COVID data Automated data scraper for Thailand COVID-19 data Accessing the Data 1st Dose Provincial Vaccination Data 2nd Dose Provincia
Random Erasing Data Augmentation. Experiments on CIFAR10, CIFAR100 and Fashion-MNIST
Random Erasing Data Augmentation =============================================================== black white random This code has the source code for
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
This repository contains the source code and data for reproducing results of Deep Continuous Clustering paper
Deep Continuous Clustering Introduction This is a Pytorch implementation of the DCC algorithms presented in the following paper (paper): Sohil Atul Sh
Convolutional 2D Knowledge Graph Embeddings resources
ConvE Convolutional 2D Knowledge Graph Embeddings resources. Paper: Convolutional 2D Knowledge Graph Embeddings Used in the paper, but do not use thes
A curated list of amazingly awesome Cybersecurity datasets
A curated list of amazingly awesome Cybersecurity datasets
GNN4Traffic - This is the repository for the collection of Graph Neural Network for Traffic Forecasting
GNN4Traffic - This is the repository for the collection of Graph Neural Network for Traffic Forecasting
A python application for manipulating pandas data frames from the comfort of your web browser
A python application for manipulating pandas data frames from the comfort of your web browser. Data flows are represented as a Directed Acyclic Graph, and nodes can be ran individually as the user sees fit.
Code release for "Self-Tuning for Data-Efficient Deep Learning" (ICML 2021)
Self-Tuning for Data-Efficient Deep Learning This repository contains the implementation code for paper: Self-Tuning for Data-Efficient Deep Learning
ReSSL: Relational Self-Supervised Learning with Weak Augmentation
ReSSL: Relational Self-Supervised Learning with Weak Augmentation This repository contains PyTorch evaluation code, training code and pretrained model
Anomaly detection on SQL data warehouses and databases
With CueObserve, you can run anomaly detection on data in your SQL data warehouses and databases. Getting Started Install via Docker docker run -p 300
IDRLnet, a Python toolbox for modeling and solving problems through Physics-Informed Neural Network (PINN) systematically.
IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver
[IJCAI-2021] A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation"
DataFree A benchmark of data-free knowledge distillation from paper "Contrastive Model Inversion for Data-Free Knowledge Distillation" Authors: Gongfa
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020)
TilinGNN: Learning to Tile with Self-Supervised Graph Neural Network (SIGGRAPH 2020) About The goal of our research problem is illustrated below: give
Deduplicating Training Data Makes Language Models Better
Deduplicating Training Data Makes Language Models Better This repository contains code to deduplicate language model datasets as descrbed in the paper
Code release for our paper, "SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo"
SimNet: Enabling Robust Unknown Object Manipulation from Pure Synthetic Data via Stereo Thomas Kollar, Michael Laskey, Kevin Stone, Brijen Thananjeyan
Utility functions for working with data from Nix in Python
Pynixutil - Utility functions for working with data from Nix in Python Examples Base32 encoding/decoding import pynixutil input = "v5sv61sszx301i0x6x
A text augmentation tool for named entity recognition.
neraug This python library helps you with augmenting text data for named entity recognition. Augmentation Example Reference from An Analysis of Simple
Python package for machine learning for healthcare using a OMOP common data model
This library was developed in order to facilitate rapid prototyping in Python of predictive machine-learning models using longitudinal medical data from an OMOP CDM-standard database.