2409 Repositories
Python keras-neural-networks Libraries
A complete end-to-end demonstration in which we collect training data in Unity and use that data to train a deep neural network to predict the pose of a cube. This model is then deployed in a simulated robotic pick-and-place task.
Object Pose Estimation Demo This tutorial will go through the steps necessary to perform pose estimation with a UR3 robotic arm in Unity. You’ll gain
(CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic
ClassSR (CVPR2021) ClassSR: A General Framework to Accelerate Super-Resolution Networks by Data Characteristic Paper Authors: Xiangtao Kong, Hengyuan
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
MMdnn MMdnn is a comprehensive and cross-framework tool to convert, visualize and diagnose deep learning (DL) models. The "MM" stands for model manage
Open standard for machine learning interoperability
Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides
PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
English | 简体中文 Welcome to the PaddlePaddle GitHub. PaddlePaddle, as the only independent R&D deep learning platform in China, has been officially open
Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.
Horovod Horovod is a distributed deep learning training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. The goal of Horovod is to make dis
Image augmentation library in Python for machine learning.
Augmentor is an image augmentation library in Python for machine learning. It aims to be a standalone library that is platform and framework independe
Hyperparameter Optimization for TensorFlow, Keras and PyTorch
Hyperparameter Optimization for Keras Talos • Key Features • Examples • Install • Support • Docs • Issues • License • Download Talos radically changes
A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation
Aboleth A bare-bones TensorFlow framework for Bayesian deep learning and Gaussian process approximation [1] with stochastic gradient variational Bayes
Bayesian dessert for Lasagne
Gelato Bayesian dessert for Lasagne Recent results in Bayesian statistics for constructing robust neural networks have proved that it is one of the be
InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
InferPy: Deep Probabilistic Modeling Made Easy InferPy is a high-level API for probabilistic modeling written in Python and capable of running on top
Deep Reinforcement Learning for Keras.
Deep Reinforcement Learning for Keras What is it? keras-rl implements some state-of-the art deep reinforcement learning algorithms in Python and seaml
Visualizer for neural network, deep learning, and machine learning models
Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX (.onnx, .pb, .pbtxt), Keras (.h5, .keras), Tens
A collection of infrastructure and tools for research in neural network interpretability.
Lucid Lucid is a collection of infrastructure and tools for research in neural network interpretability. We're not currently supporting tensorflow 2!
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
Transfer Learning library for Deep Neural Networks.
Transfer and meta-learning in Python Each folder in this repository corresponds to a method or tool for transfer/meta-learning. xfer-ml is a standalon
Gluon CV Toolkit
Gluon CV Toolkit | Installation | Documentation | Tutorials | GluonCV provides implementations of the state-of-the-art (SOTA) deep learning models in
A clear, concise, simple yet powerful and efficient API for deep learning.
The Gluon API Specification The Gluon API specification is an effort to improve speed, flexibility, and accessibility of deep learning technology for
QKeras: a quantization deep learning library for Tensorflow Keras
QKeras github.com/google/qkeras QKeras 0.8 highlights: Automatic quantization using QKeras; Stochastic behavior (including stochastic rouding) is disa
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
Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser.
Hera Train/evaluate a Keras model, get metrics streamed to a dashboard in your browser. Setting up Step 1. Plant the spy Install the package pip
Distributed Deep learning with Keras & Spark
Elephas: Distributed Deep Learning with Keras & Spark Elephas is an extension of Keras, which allows you to run distributed deep learning models at sc
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
This project is now archived. It's been fun working on it, but it's time for me to move on. Thank you for all the support and feedback over the last c
Keras community contributions
keras-contrib : Keras community contributions Keras-contrib is deprecated. Use TensorFlow Addons. The future of Keras-contrib: We're migrating to tens
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
Machine Learning Platform for Kubernetes
Reproduce, Automate, Scale your data science. Welcome to Polyaxon, a platform for building, training, and monitoring large scale deep learning applica
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
Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥
TensorLayer is a novel TensorFlow-based deep learning and reinforcement learning library designed for researchers and engineers. It provides an extens
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
Simple tools for logging and visualizing, loading and training
TNT TNT is a library providing powerful dataloading, logging and visualization utilities for Python. It is closely integrated with PyTorch and is desi
A scikit-learn compatible neural network library that wraps PyTorch
A scikit-learn compatible neural network library that wraps PyTorch. Resources Documentation Source Code Examples To see more elaborate examples, look
A simplified framework and utilities for PyTorch
Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne
High performance implementation of Extreme Learning Machines (fast randomized neural networks).
High Performance toolbox for Extreme Learning Machines. Extreme learning machines (ELM) are a particular kind of Artificial Neural Networks, which sol
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
50% faster, 50% less RAM Machine Learning. Numba rewritten Sklearn. SVD, NNMF, PCA, LinearReg, RidgeReg, Randomized, Truncated SVD/PCA, CSR Matrices all 50+% faster
[Due to the time taken @ uni, work + hell breaking loose in my life, since things have calmed down a bit, will continue commiting!!!] [By the way, I'm
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
GANsformer: Generative Adversarial Transformers Drew A
GANsformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick *I wish to thank Christopher D. Manning for the fruitf
PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 2021
Neural Scene Flow Fields PyTorch implementation of paper "Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes", CVPR 20
An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding, top-down-bottom-up, and attention (consensus between columns)
GLOM - Pytorch (wip) An attempt at the implementation of Glom, Geoffrey Hinton's new idea that integrates neural fields, predictive coding,
LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search
LightSpeech UnOfficial PyTorch implementation of LightSpeech: Lightweight and Fast Text to Speech with Neural Architecture Search.
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
A Python library that helps data scientists to infer causation rather than observing correlation.
A Python library that helps data scientists to infer causation rather than observing correlation.
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.
Social Distancing Detector using deep learning and capable to run on edge AI devices such as NVIDIA Jetson, Google Coral, and more.
Smart Social Distancing Smart Social Distancing Introduction Getting Started Prerequisites Usage Processor Optional Parameters Configuring AWS credent
Implements Gradient Centralization and allows it to use as a Python package in TensorFlow
Gradient Centralization TensorFlow This Python package implements Gradient Centralization in TensorFlow, a simple and effective optimization technique
Sandwich Batch Normalization
Sandwich Batch Normalization Code for Sandwich Batch Normalization. Introduction We present Sandwich Batch Normalization (SaBN), an extremely easy imp
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.
Autonomous Driving project for Euro Truck Simulator 2
hope-autonomous-driving Autonomous Driving project for Euro Truck Simulator 2 Video: How is it working ? In this video, the program processes the imag
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
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".
Neural Re-rendering for Full-frame Video Stabilization
NeRViS: Neural Re-rendering for Full-frame Video Stabilization Project Page | Video | Paper | Google Colab Setup Setup environment for [Yu and Ramamoo
NeRViS: Neural Re-rendering for Full-frame Video Stabilization
Neural Re-rendering for Full-frame Video Stabilization
Human head pose estimation using Keras over TensorFlow.
RealHePoNet: a robust single-stage ConvNet for head pose estimation in the wild.
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
Facilitating the design, comparison and sharing of deep text matching models.
MatchZoo Facilitating the design, comparison and sharing of deep text matching models. MatchZoo 是一个通用的文本匹配工具包,它旨在方便大家快速的实现、比较、以及分享最新的深度文本匹配模型。 🔥 News
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.
anaGo anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as nam
Topic Modelling for Humans
gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ
An Open-Source Package for Neural Relation Extraction (NRE)
OpenNRE We have a DEMO website (http://opennre.thunlp.ai/). Try it out! OpenNRE is an open-source and extensible toolkit that provides a unified frame
🏖 Easy training and deployment of seq2seq models.
Headliner Headliner is a sequence modeling library that eases the training and in particular, the deployment of custom sequence models for both resear
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
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
NeMo: a toolkit for conversational AI
NVIDIA NeMo Introduction NeMo is a toolkit for creating Conversational AI applications. NeMo product page. Introductory video. The toolkit comes with
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
Basic Utilities for PyTorch Natural Language Processing (NLP)
Basic Utilities for PyTorch Natural Language Processing (NLP) PyTorch-NLP, or torchnlp for short, is a library of basic utilities for PyTorch NLP. tor
✨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
⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡
Translations 🇩🇪 DE 🇫🇷 FR 🇭🇺 HU 🇮🇩 ID 🇮🇹 IT 🇳🇱 NL 🇧🇷 PT-BR 🇷🇺 RU 🇨🇳 ZH ➡️ Documentation | Discord | Installation Guide ⬅️ Fully autom
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
textgenrnn Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly tr
:mag: End-to-End Framework for building natural language search interfaces to data by utilizing Transformers and the State-of-the-Art of NLP. Supporting DPR, Elasticsearch, HuggingFace’s Modelhub and much more!
Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases. Whether you want
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
An easier way to build neural search on the cloud
An easier way to build neural search on the cloud Jina is a deep learning-powered search framework for building cross-/multi-modal search systems (e.g
Open Source Neural Machine Translation in PyTorch
OpenNMT-py: Open-Source Neural Machine Translation OpenNMT-py is the PyTorch version of the OpenNMT project, an open-source (MIT) neural machine trans
Unsupervised text tokenizer for Neural Network-based text generation.
SentencePiece SentencePiece is an unsupervised text tokenizer and detokenizer mainly for Neural Network-based text generation systems where the vocabu
💫 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
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
⚠️ Checkout develop branch to see what is coming in pyannote.audio 2.0: a much smaller and cleaner codebase Python-first API (the good old pyannote-au
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
kapre: Keras Audio Preprocessors
Kapre Keras Audio Preprocessors - compute STFT, ISTFT, Melspectrogram, and others on GPU real-time. Tested on Python 3.6 and 3.7 Why Kapre? vs. Pre-co
Ivy is a templated deep learning framework which maximizes the portability of deep learning codebases.
Ivy is a templated deep learning framework which maximizes the portability of deep learning codebases. Ivy wraps the functional APIs of existing frameworks. Framework-agnostic functions, libraries and layers can then be written using Ivy, with simultaneous support for all frameworks. Ivy currently supports Jax, TensorFlow, PyTorch, MXNet and Numpy. Check out the docs for more info!
A neural-based binary analysis tool
A neural-based binary analysis tool Introduction This directory contains the demo of a neural-based binary analysis tool. We test the framework using
Open source repository for the code accompanying the paper 'Non-Rigid Neural Radiance Fields Reconstruction and Novel View Synthesis of a Deforming Scene from Monocular Video'.
Non-Rigid Neural Radiance Fields This is the official repository for the project "Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synt
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
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.
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
An assignment on creating a minimalist neural network toolkit for CS11-747
minnn by Graham Neubig, Zhisong Zhang, and Divyansh Kaushik This is an exercise in developing a minimalist neural network toolkit for NLP, part of Car
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
这是一个mobilenet-yolov4-lite的库,把yolov4主干网络修改成了mobilenet,修改了Panet的卷积组成,使参数量大幅度缩小。
YOLOV4:You Only Look Once目标检测模型-修改mobilenet系列主干网络-在Keras当中的实现 2021年2月8日更新: 加入letterbox_image的选项,关闭letterbox_image后网络的map一般可以得到提升。
Construct a neural network frame by Numpy
本项目的CSDN博客链接:https://blog.csdn.net/weixin_41578567/article/details/111482022 1. 概览 本项目主要用于神经网络的学习,通过基于numpy的实现,了解神经网络底层前向传播、反向传播以及各类优化器的原理。 该项目目前已实现的功
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
Facilitating the design, comparison and sharing of deep text matching models.
MatchZoo Facilitating the design, comparison and sharing of deep text matching models. MatchZoo 是一个通用的文本匹配工具包,它旨在方便大家快速的实现、比较、以及分享最新的深度文本匹配模型。 🔥 News
Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition, Part-of-Speech Tagging and so on.
anaGo anaGo is a Python library for sequence labeling(NER, PoS Tagging,...), implemented in Keras. anaGo can solve sequence labeling tasks such as nam
Topic Modelling for Humans
gensim – Topic Modelling in Python Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. Targ
An Open-Source Package for Neural Relation Extraction (NRE)
OpenNRE We have a DEMO website (http://opennre.thunlp.ai/). Try it out! OpenNRE is an open-source and extensible toolkit that provides a unified frame