2114 Repositories
Python graph-attention-networks Libraries
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
SSD: Single Shot MultiBox Detector pytorch implementation focusing on simplicity
SSD: Single Shot MultiBox Detector Introduction Here is my pytorch implementation of 2 models: SSD-Resnet50 and SSDLite-MobilenetV2.
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.
Implementation of Nyström Self-attention, from the paper Nyströmformer
Nyström Attention Implementation of Nyström Self-attention, from the paper Nyströmformer. Yannic Kilcher video Install $ pip install nystrom-attention
BitPack is a practical tool to efficiently save ultra-low precision/mixed-precision quantized models.
BitPack is a practical tool that can efficiently save quantized neural network models with mixed bitwidth.
BaseSpec is a system that performs a comparative analysis of baseband implementation and the specifications of cellular networks.
BaseSpec is a system that performs a comparative analysis of baseband implementation and the specifications of cellular networks. The key intuition of BaseSpec is that a message decoder in baseband software embeds the protocol specification in a machine-friendly structure to parse incoming messages;
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.
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.
Learning to Initialize Neural Networks for Stable and Efficient Training
GradInit This repository hosts the code for experiments in the paper, GradInit: Learning to Initialize Neural Networks for Stable and Efficient Traini
Implementation of self-attention mechanisms for general purpose. Focused on computer vision modules. Ongoing repository.
Self-attention building blocks for computer vision applications in PyTorch Implementation of self attention mechanisms for computer vision in PyTorch
Puzzle-CAM: Improved localization via matching partial and full features.
Puzzle-CAM The official implementation of "Puzzle-CAM: Improved localization via matching partial and full features".
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.
计算机视觉中用到的注意力模块和其他即插即用模块PyTorch Implementation Collection of Attention Module and Plug&Play Module
PyTorch实现多种计算机视觉中网络设计中用到的Attention机制,还收集了一些即插即用模块。由于能力有限精力有限,可能很多模块并没有包括进来,有任何的建议或者改进,可以提交issue或者进行PR。
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+.
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
✨Fast Coreference Resolution in spaCy with Neural Networks
✨ NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolv
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
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
💫 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
Dimensionality reduction in very large datasets using Siamese Networks
ivis Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets. Ivis
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
DeepSpeech is an open source embedded (offline, on-device) speech-to-text engine which can run in real time on devices ranging from a Raspberry Pi 4 to high power GPU servers.
Project DeepSpeech DeepSpeech is an open-source Speech-To-Text engine, using a model trained by machine learning techniques based on Baidu's Deep Spee
text_recognition_toolbox: The reimplementation of a series of classical scene text recognition papers with Pytorch in a uniform way.
text recognition toolbox 1. 项目介绍 该项目是基于pytorch深度学习框架,以统一的改写方式实现了以下6篇经典的文字识别论文,论文的详情如下。该项目会持续进行更新,欢迎大家提出问题以及对代码进行贡献。 模型 论文标题 发表年份 模型方法划分 CRNN 《An End-t
Official implementation of the ICLR 2021 paper
You Only Need Adversarial Supervision for Semantic Image Synthesis Official PyTorch implementation of the ICLR 2021 paper "You Only Need Adversarial S
Implementation of TabTransformer, attention network for tabular data, in Pytorch
Tab Transformer Implementation of Tab Transformer, attention network for tabular data, in Pytorch. This simple architecture came within a hair's bread
Efficient 3D Backbone Network for Temporal Modeling
VoV3D is an efficient and effective 3D backbone network for temporal modeling implemented on top of PySlowFast. Diverse Temporal Aggregation and
Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks
SA-Net: Shuffle Attention for Deep Convolutional Neural Networks (paper) By Qing-Long Zhang and Yu-Bin Yang [State Key Laboratory for Novel Software T
[ICLR'21] Counterfactual Generative Networks
This repository contains the code for the ICLR 2021 paper "Counterfactual Generative Networks" by Axel Sauer and Andreas Geiger. If you want to take the CGN for a spin and generate counterfactual images, you can try out the Colab below.
Authors implementation of LieTransformer: Equivariant Self-Attention for Lie Groups
LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant self-at
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.
Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping
Keras implementation of Normalizer-Free Networks and SGD - Adaptive Gradient Clipping
Efficient neural networks for analog audio effect modeling
micro-TCN Efficient neural networks for audio effect modeling
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sockeye This package contains the Sockeye project, an open-source sequence-to-sequence framework for Neural Machine Translation based on Apache MXNet
A model library for exploring state-of-the-art deep learning topologies and techniques for optimizing Natural Language Processing neural networks
A Deep Learning NLP/NLU library by Intel® AI Lab Overview | Models | Installation | Examples | Documentation | Tutorials | Contributing NLP Architect
✨Fast Coreference Resolution in spaCy with Neural Networks
✨ NeuralCoref 4.0: Coreference Resolution in spaCy with Neural Networks. NeuralCoref is a pipeline extension for spaCy 2.1+ which annotates and resolv
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
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
💫 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
Dimensionality reduction in very large datasets using Siamese Networks
ivis Implementation of the ivis algorithm as described in the paper Structure-preserving visualisation of high dimensional single-cell datasets. Ivis
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
NeuPy is a Tensorflow based python library for prototyping and building neural networks
NeuPy v0.8.2 NeuPy is a python library for prototyping and building neural networks. NeuPy uses Tensorflow as a computational backend for deep learnin
Lightweight library to build and train neural networks in Theano
Lasagne Lasagne is a lightweight library to build and train neural networks in Theano. Its main features are: Supports feed-forward networks such as C
JAX-based neural network library
Haiku: Sonnet for JAX Overview | Why Haiku? | Quickstart | Installation | Examples | User manual | Documentation | Citing Haiku What is Haiku? Haiku i
Fast and Easy Infinite Neural Networks in Python
Neural Tangents ICLR 2020 Video | Paper | Quickstart | Install guide | Reference docs | Release notes Overview Neural Tangents is a high-level neural
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
Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.
Translated in 🇰🇷 Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
TL;DR Ignite is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. Click on the image to
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
CNTK Chat Windows build status Linux build status The Microsoft Cognitive Toolkit (https://cntk.ai) is a unified deep learning toolkit that describes
TensorFlow-based neural network library
Sonnet Documentation | Examples Sonnet is a library built on top of TensorFlow 2 designed to provide simple, composable abstractions for machine learn
A Neural Net Training Interface on TensorFlow, with focus on speed + flexibility
Tensorpack is a neural network training interface based on TensorFlow. Features: It's Yet Another TF high-level API, with speed, and flexibility built
A flexible framework of neural networks for deep learning
Chainer: A deep learning framework Website | Docs | Install Guide | Tutorials (ja) | Examples (Official, External) | Concepts | ChainerX Forum (en, ja
Deep Learning for humans
Keras: Deep Learning for Python Under Construction In the near future, this repository will be used once again for developing the Keras codebase. For
Tensors and Dynamic neural networks in Python with strong GPU acceleration
PyTorch is a Python package that provides two high-level features: Tensor computation (like NumPy) with strong GPU acceleration Deep neural networks b
An Open Source Machine Learning Framework for Everyone
Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, 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
🔎 Hunt down social media accounts by username across social networks
Hunt down social media accounts by username across social networks Installation | Usage | Docker Notes | Contributing Installation # clone the repo $
Implementation of Feedback Transformer in Pytorch
Feedback Transformer - Pytorch Simple implementation of Feedback Transformer in Pytorch. They improve on Transformer-XL by having each token have acce
FcaNet: Frequency Channel Attention Networks
FcaNet: Frequency Channel Attention Networks PyTorch implementation of the paper "FcaNet: Frequency Channel Attention Networks". Simplest usage Models
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model
Only a Matter of Style: Age Transformation Using a Style-Based Regression Model The task of age transformation illustrates the change of an individual
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
DALL-E in Pytorch Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch. It will also contain CLIP for ranking the ge
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
A simple command line tool for text to image generation, using OpenAI's CLIP and a BigGAN
artificial intelligence cosmic love and attention fire in the sky a pyramid made of ice a lonely house in the woods marriage in the mountains lantern
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting
Informer: Beyond Efficient Transformer for Long Sequence Time-Series Forecasting This is the origin Pytorch implementation of Informer in the followin
Implementation of the Point Transformer layer, in Pytorch
Point Transformer - Pytorch Implementation of the Point Transformer self-attention layer, in Pytorch. The simple circuit above seemed to have allowed
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
SWA Object Detection
SWA Object Detection This project hosts the scripts for training SWA object detectors, as presented in our paper: @article{zhang2020swa, title={SWA
State of the Art Neural Networks for Deep Learning
pyradox This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2
Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch.
SE3 Transformer - Pytorch Implementation of SE3-Transformers for Equivariant Self-Attention, in Pytorch. May be needed for replicating Alphafold2 resu
Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch
Lie Transformer - Pytorch (wip) Implementation of Lie Transformer, Equivariant Self-Attention, in Pytorch. Only the SE3 version will be present in thi
Sample code from the Neural Networks from Scratch book.
Neural Networks from Scratch (NNFS) book code Code from the NNFS book (https://nnfs.io) separated by chapter.
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).
Transformers are Graph Neural Networks!
🚀 Gated Graph Transformers Gated Graph Transformers for graph-level property prediction, i.e. graph classification and regression. Associated article
Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Networks
CyGNet This repository reproduces the AAAI'21 paper “Learning from History: Modeling Temporal Knowledge Graphs with Sequential Copy-Generation Network
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
A customisable 3D platform for agent-based AI research
DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a
Backtest 1000s of minute-by-minute trading algorithms for training AI with automated pricing data from: IEX, Tradier and FinViz. Datasets and trading performance automatically published to S3 for building AI training datasets for teaching DNNs how to trade. Runs on Kubernetes and docker-compose. 150 million trading history rows generated from +5000 algorithms. Heads up: Yahoo's Finance API was disabled on 2019-01-03 https://developer.yahoo.com/yql/
Stock Analysis Engine Build and tune investment algorithms for use with artificial intelligence (deep neural networks) with a distributed stack for ru
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
Emulator for rapid prototyping of Software Defined Networks
Mininet: Rapid Prototyping for Software Defined Networks The best way to emulate almost any network on your laptop! Mininet 2.3.0b2 What is Mininet? M
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
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
NeuroNER NeuroNER is a program that performs named-entity recognition (NER). Website: neuroner.com. This page gives step-by-step instructions to insta
💫 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
Lightwood is Legos for Machine Learning.
Lightwood is like Legos for Machine Learning. A Pytorch based framework that breaks down machine learning problems into smaller blocks that can be glu
Machine learning, in numpy
numpy-ml Ever wish you had an inefficient but somewhat legible collection of machine learning algorithms implemented exclusively in NumPy? No? Install
StellarGraph - Machine Learning on Graphs
StellarGraph Machine Learning Library StellarGraph is a Python library for machine learning on graphs and networks. Table of Contents Introduction Get
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.
pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit
Code samples for my book "Neural Networks and Deep Learning"
Code samples for "Neural Networks and Deep Learning" This repository contains code samples for my book on "Neural Networks and Deep Learning". The cod
An Open Source Machine Learning Framework for Everyone
Documentation TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, a
Image-to-Image Translation with Conditional Adversarial Networks (Pix2pix) implementation in keras
pix2pix-keras Pix2pix implementation in keras. Original paper: Image-to-Image Translation with Conditional Adversarial Networks (pix2pix) Paper Author