1311 Repositories
Python graph-classification Libraries
Implicit Graph Neural Networks
Implicit Graph Neural Networks This repository is the official PyTorch implementation of "Implicit Graph Neural Networks". Fangda Gu*, Heng Chang*, We
Learning Intents behind Interactions with Knowledge Graph for Recommendation, WWW2021
Learning Intents behind Interactions with Knowledge Graph for Recommendation This is our PyTorch implementation for the paper: Xiang Wang, Tinglin Hua
Implement face detection, and age and gender classification, and emotion classification.
YOLO Keras Face Detection Implement Face detection, and Age and Gender Classification, and Emotion Classification. (image from wider face dataset) Ove
Dogs classification with Deep Metric Learning using some popular losses
Tsinghua Dogs classification with Deep Metric Learning 1. Introduction Tsinghua Dogs dataset Tsinghua Dogs is a fine-grained classification dataset fo
Functional TensorFlow Implementation of Singular Value Decomposition for paper Fast Graph Learning
tf-fsvd TensorFlow Implementation of Functional Singular Value Decomposition for paper Fast Graph Learning with Unique Optimal Solutions Cite If you f
Official implementation of Self-supervised Graph Attention Networks (SuperGAT), ICLR 2021.
SuperGAT Official implementation of Self-supervised Graph Attention Networks (SuperGAT). This model is presented at How to Find Your Friendly Neighbor
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP
Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification.
Easy Few-Shot Learning Ready-to-use code and tutorial notebooks to boost your way into few-shot image classification. This repository is made for you
Fast image augmentation library and easy to use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about library: https://www.mdpi.com/2078-2489/11/2/125
Albumentations Albumentations is a Python library for image augmentation. Image augmentation is used in deep learning and computer vision tasks to inc
Scikit-learn compatible estimation of general graphical models
skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships
Python Library for Model Interpretation/Explanations
Skater Skater is a unified framework to enable Model Interpretation for all forms of model to help one build an Interpretable machine learning system
Gluon CV Toolkit
Gluon CV Toolkit | Installation | Documentation | Tutorials | GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in
Graph Neural Networks with Keras and Tensorflow 2.
Welcome to Spektral Spektral is a Python library for graph deep learning, based on the Keras API and TensorFlow 2. The main goal of this project is to
Geometric Deep Learning Extension Library for PyTorch
Documentation | Paper | Colab Notebooks | External Resources | OGB Examples PyTorch Geometric (PyG) is a geometric deep learning extension library for
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
ThunderSVM: A Fast SVM Library on GPUs and CPUs
What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss
Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
Python Extreme Learning Machine (ELM) Python Extreme Learning Machine (ELM) is a machine learning technique used for classification/regression tasks.
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
A machine learning toolkit dedicated to time-series data
tslearn The machine learning toolkit for time series analysis in Python Section Description Installation Installing the dependencies and tslearn Getti
Little Ball of Fur - A graph sampling extension library for NetworKit and NetworkX (CIKM 2020)
Little Ball of Fur is a graph sampling extension library for Python. Please look at the Documentation, relevant Paper, Promo video and External Resour
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
A scikit-learn based module for multi-label et. al. classification
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
EGNN - Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch
EGNN - Pytorch Implementation of E(n)-Equivariant Graph Neural Networks, in Pytorch. May be eventually used for Alphafold2 replication. This
Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image classification, in Pytorch
Transformer in Transformer Implementation of Transformer in Transformer, pixel level attention paired with patch level attention for image c
Implementation of E(n)-Transformer, which extends the ideas of Welling's E(n)-Equivariant Graph Neural Network to attention
E(n)-Equivariant Transformer (wip) Implementation of E(n)-Equivariant Transformer, which extends the ideas from Welling's E(n)-Equivariant G
🍊 :bar_chart: :bulb: Orange: Interactive data analysis
Orange Data Mining Orange is a data mining and visualization toolbox for novice and expert alike. To explore data with Orange, one requires no program
A Python library created to assist programmers with complex mathematical functions
libmaths was created not only as a learning experience for me, but as a way to make mathematical models in seconds for Python users using mat
This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).
Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre
Generate a roam research like Network Graph view from your Notion pages.
Notion Graph View Export Notion pages to a Roam Research like graph view.
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing"
A PyTorch implementation of "Pathfinder Discovery Networks for Neural Message Passing" (WebConf 2021). Abstract In this work we propose Pathfind
Deepfake Scanner by Deepware.
Deepware Scanner (CLI) This repository contains the command-line deepfake scanner tool with the pre-trained models that are currently used at deepware
Implementation of TimeSformer, a pure attention-based solution for video classification
TimeSformer - Pytorch Implementation of TimeSformer, a pure and simple attention-based solution for reaching SOTA on video classification.
Official PyTorch implementation of Joint Object Detection and Multi-Object Tracking with Graph Neural Networks
This is the official PyTorch implementation of our paper: "Joint Object Detection and Multi-Object Tracking with Graph Neural Networks". Our project website and video demos are here.
A command line utility for tracking a stock market portfolio. Primarily featuring high resolution braille graphs.
A command line stock market / portfolio tracker originally insipred by Ericm's Stonks program, featuring unicode for incredibly high detailed graphs even in a terminal.
Plots is a graph plotting app for GNOME.
Plots is a graph plotting app for GNOME. Plots makes it easy to visualise mathematical formulae. In addition to basic arithmetic operations, it supports trigonometric, hyperbolic, exponential and logarithmic functions, as well as arbitrary sums and products.Plots is designed to integrate well with the GNOME desktop and takes advantage of modern hardware using OpenGL, and currently supports OpenGL 3.3+.
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag
Get list of common stop words in various languages in Python
Python Stop Words Table of contents Overview Available languages Installation Basic usage Python compatibility Overview Get list of common stop words
Text vectorization tool to outperform TFIDF for classification tasks
WHAT: Supervised text vectorization tool Textvec is a text vectorization tool, with the aim to implement all the "classic" text vectorization NLP meth
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you
DELTA is a deep learning based natural language and speech processing platform.
DELTA - A DEep learning Language Technology plAtform What is DELTA? DELTA is a deep learning based end-to-end natural language and speech processing p
Snips Python library to extract meaning from text
Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur
Python implementation of TextRank for phrase extraction and summarization of text documents
PyTextRank PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, used to: extract the top-ranked phrases from text document
fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.
fastNLP fastNLP是一款轻量级的自然语言处理(NLP)工具包,目标是快速实现NLP任务以及构建复杂模型。 fastNLP具有如下的特性: 统一的Tabular式数据容器,简化数据预处理过程; 内置多种数据集的Loader和Pipe,省去预处理代码; 各种方便的NLP工具,例如Embedd
An open source library for deep learning end-to-end dialog systems and chatbots.
DeepPavlov is an open-source conversational AI library built on TensorFlow, Keras and PyTorch. DeepPavlov is designed for development of production re
Library for fast text representation and classification.
fastText fastText is a library for efficient learning of word representations and sentence classification. Table of contents Resources Models Suppleme
💫 Industrial-strength Natural Language Processing (NLP) in Python
spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc
The interactive graphing library for Python (includes Plotly Express) :sparkles:
plotly.py Latest Release User forum PyPI Downloads License Data Science Workspaces Our recommended IDE for Plotly’s Python graphing library is Dash En
Python Audio Analysis Library: Feature Extraction, Classification, Segmentation and Applications
A Python library for audio feature extraction, classification, segmentation and applications This doc contains general info. Click here for the comple
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
This is a Pytorch implementation of the paper: Self-Supervised Graph Transformer on Large-Scale Molecular Data.
NFNets and Adaptive Gradient Clipping for SGD implemented in PyTorch
PyTorch implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping Paper: https://arxiv.org/abs/2102.06171.pdf Original code: htt
Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Summarization, translation, Q&A, text generation and more at blazing speed using a T5 version implemented in ONNX. This package is still in alpha stag
Get list of common stop words in various languages in Python
Python Stop Words Table of contents Overview Available languages Installation Basic usage Python compatibility Overview Get list of common stop words
Text vectorization tool to outperform TFIDF for classification tasks
WHAT: Supervised text vectorization tool Textvec is a text vectorization tool, with the aim to implement all the "classic" text vectorization NLP meth
Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.
Kashgari Overview | Performance | Installation | Documentation | Contributing 🎉 🎉 🎉 We released the 2.0.0 version with TF2 Support. 🎉 🎉 🎉 If you
DELTA is a deep learning based natural language and speech processing platform.
DELTA - A DEep learning Language Technology plAtform What is DELTA? DELTA is a deep learning based end-to-end natural language and speech processing p
Snips Python library to extract meaning from text
Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur
Python implementation of TextRank for phrase extraction and summarization of text documents
PyTextRank PyTextRank is a Python implementation of TextRank as a spaCy pipeline extension, used to: extract the top-ranked phrases from text document
fastNLP: A Modularized and Extensible NLP Framework. Currently still in incubation.
fastNLP fastNLP是一款轻量级的自然语言处理(NLP)工具包,目标是快速实现NLP任务以及构建复杂模型。 fastNLP具有如下的特性: 统一的Tabular式数据容器,简化数据预处理过程; 内置多种数据集的Loader和Pipe,省去预处理代码; 各种方便的NLP工具,例如Embedd
An open source library for deep learning end-to-end dialog systems and chatbots.
DeepPavlov is an open-source conversational AI library built on TensorFlow, Keras and PyTorch. DeepPavlov is designed for development of production re
Library for fast text representation and classification.
fastText fastText is a library for efficient learning of word representations and sentence classification. Table of contents Resources Models Suppleme
💫 Industrial-strength Natural Language Processing (NLP) in Python
spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc
The interactive graphing library for Python (includes Plotly Express) :sparkles:
plotly.py Latest Release User forum PyPI Downloads License Data Science Workspaces Our recommended IDE for Plotly’s Python graphing library is Dash En
Learning embeddings for classification, retrieval and ranking.
StarSpace StarSpace is a general-purpose neural model for efficient learning of entity embeddings for solving a wide variety of problems: Learning wor
ThunderSVM: A Fast SVM Library on GPUs and CPUs
What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss
ktrain is a Python library that makes deep learning and AI more accessible and easier to apply
Overview | Tutorials | Examples | Installation | FAQ | How to Cite Welcome to ktrain News and Announcements 2020-11-08: ktrain v0.25.x is released and
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Website | Documentation | Tutorials | Installation | Release Notes CatBoost is a machine learning method based on gradient boosting over decision tree
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Visual profiler for Python
vprof vprof is a Python package providing rich and interactive visualizations for various Python program characteristics such as running time and memo
:package: :fire: Python project management. Manage packages: convert between formats, lock, install, resolve, isolate, test, build graph, show outdated, audit. Manage venvs, build package, bump version.
THE PROJECT IS ARCHIVED Forks: https://github.com/orsinium/forks DepHell -- project management for Python. Why it is better than all other tools: Form
A Static Analysis Tool for Detecting Security Vulnerabilities in Python Web Applications
This project is no longer maintained March 2020 Update: Please go see the amazing Pysa tutorial that should get you up to speed finding security vulne
Neo4j Bolt driver for Python
Neo4j Bolt Driver for Python This repository contains the official Neo4j driver for Python. Each driver release (from 4.0 upwards) is built specifical
Python library for serializing any arbitrary object graph into JSON. It can take almost any Python object and turn the object into JSON. Additionally, it can reconstitute the object back into Python.
jsonpickle jsonpickle is a library for the two-way conversion of complex Python objects and JSON. jsonpickle builds upon the existing JSON encoders, s
A python module to parse the Open Graph Protocol
OpenGraph is a module of python for parsing the Open Graph Protocol, you can read more about the specification at http://ogp.me/ Installation $ pip in
Facebook open graph api implementation using the Django web framework in python
Django Facebook by Thierry Schellenbach (mellowmorning.com) Status Django and Facebook are both rapidly changing at the moment. Meanwhile, I'm caught
NLP Core Library and Model Zoo based on PaddlePaddle 2.0
PaddleNLP 2.0拥有丰富的模型库、简洁易用的API与高性能的分布式训练的能力,旨在为飞桨开发者提升文本建模效率,并提供基于PaddlePaddle 2.0的NLP领域最佳实践。
PyTorch code for the paper: FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning
FeatMatch: Feature-Based Augmentation for Semi-Supervised Learning This is the PyTorch implementation of our paper: FeatMatch: Feature-Based Augmentat
This is a simple graph database in SQLite, inspired by
This is a simple graph database in SQLite, inspired by "SQLite as a document database".
Implementation of Bottleneck Transformer in Pytorch
Bottleneck Transformer - Pytorch Implementation of Bottleneck Transformer, SotA visual recognition model with convolution + attention that outperforms
Graph Transformer Architecture. Source code for
Graph Transformer Architecture Source code for the paper "A Generalization of Transformer Networks to Graphs" by Vijay Prakash Dwivedi and Xavier Bres
Bottleneck Transformers for Visual Recognition
Bottleneck Transformers for Visual Recognition Experiments Model Params (M) Acc (%) ResNet50 baseline (ref) 23.5M 93.62 BoTNet-50 18.8M 95.11% BoTNet-
TDN: Temporal Difference Networks for Efficient Action Recognition
TDN: Temporal Difference Networks for Efficient Action Recognition Overview We release the PyTorch code of the TDN(Temporal Difference Networks).
For holding anime-related object classification and detection models
Animesion An end-to-end framework for anime-related object classification, detection, segmentation, and other models. Update: 01/22/2020. Due to time-
Transformers are Graph Neural Networks!
🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article
Graph neural network message passing reframed as a Transformer with local attention
Adjacent Attention Network An implementation of a simple transformer that is equivalent to graph neural network where the message passing is done with
Official PyTorch implementation for paper Context Matters: Graph-based Self-supervised Representation Learning for Medical Images
Context Matters: Graph-based Self-supervised Representation Learning for Medical Images Official PyTorch implementation for paper Context Matters: Gra
Official implementation of AAAI-21 paper "Label Confusion Learning to Enhance Text Classification Models"
Description: This is the official implementation of our AAAI-21 accepted paper Label Confusion Learning to Enhance Text Classification Models. The str
CCF BDCI 2020 房产行业聊天问答匹配赛道 A榜47/2985
CCF BDCI 2020 房产行业聊天问答匹配 A榜47/2985 赛题描述详见:https://www.datafountain.cn/competitions/474 文件说明 data: 存放训练数据和测试数据以及预处理代码 model_bert.py: 网络模型结构定义 adv_train
Official Python client for the MonkeyLearn API. Build and consume machine learning models for language processing from your Python apps.
MonkeyLearn API for Python Official Python client for the MonkeyLearn API. Build and run machine learning models for language processing from your Pyt
A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
Light Gradient Boosting Machine LightGBM is a gradient boosting framework that uses tree based learning algorithms. It is designed to be distributed a
Python SDK for Facebook's Graph API
Facebook Python SDK This client library is designed to support the Facebook Graph API and the official Facebook JavaScript SDK, which is the canonical
Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020)
Karate Club is an unsupervised machine learning extension library for NetworkX. Please look at the Documentation, relevant Paper, Promo Video, and Ext
Multi-class confusion matrix library in Python
Table of contents Overview Installation Usage Document Try PyCM in Your Browser Issues & Bug Reports Todo Outputs Dependencies Contribution References
An open source library for deep learning end-to-end dialog systems and chatbots.
DeepPavlov is an open-source conversational AI library built on TensorFlow, Keras and PyTorch. DeepPavlov is designed for development of production re
Snips Python library to extract meaning from text
Snips NLU Snips NLU (Natural Language Understanding) is a Python library that allows to extract structured information from sentences written in natur
💫 Industrial-strength Natural Language Processing (NLP) in Python
spaCy: Industrial-strength NLP spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest researc
A Python package implementing a new model for text classification with visualization tools for Explainable AI :octocat:
A Python package implementing a new model for text classification with visualization tools for Explainable AI 🍣 Online live demos: http://tworld.io/s
A unified framework for machine learning with time series
Welcome to sktime A unified framework for machine learning with time series We provide specialized time series algorithms and scikit-learn compatible
Accelerated deep learning R&D
Accelerated deep learning R&D PyTorch framework for Deep Learning research and development. It focuses on reproducibility, rapid experimentation, and