2462 Repositories
Python low-resource-machine-translation Libraries
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom
Neural Turing Machine (NTM) & Differentiable Neural Computer (DNC) with pytorch & visdom Sample on-line plotting while training(avg loss)/testing(writ
Accelerate Neural Net Training by Progressively Freezing Layers
FreezeOut A simple technique to accelerate neural net training by progressively freezing layers. This repository contains code for the extended abstra
Sequence-to-Sequence learning using PyTorch
Seq2Seq in PyTorch This is a complete suite for training sequence-to-sequence models in PyTorch. It consists of several models and code to both train
PyTorch Implementation of [1611.06440] Pruning Convolutional Neural Networks for Resource Efficient Inference
PyTorch implementation of [1611.06440 Pruning Convolutional Neural Networks for Resource Efficient Inference] This demonstrates pruning a VGG16 based
Unsupervised Image-to-Image Translation
UNIT: UNsupervised Image-to-image Translation Networks Imaginaire Repository We have a reimplementation of the UNIT method that is more performant. It
A PyTorch implementation of a Factorization Machine module in cython.
fmpytorch A library for factorization machines in pytorch. A factorization machine is like a linear model, except multiplicative interaction terms bet
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
Unofficial Alias-Free GAN implementation. Based on rosinality's version with expanded training and inference options.
Alias-Free GAN An unofficial version of Alias-Free Generative Adversarial Networks (https://arxiv.org/abs/2106.12423). This repository was heavily bas
Python library for the DeepL language translation API.
The DeepL API is a language translation API that allows other computer programs to send texts and documents to DeepL's servers and receive high-quality translations. This opens a whole universe of opportunities for developers: any translation product you can imagine can now be built on top of DeepL's best-in-class translation technology.
An open-source, low-cost, image-based weed detection device for fallow scenarios.
Welcome to the OpenWeedLocator (OWL) project, an opensource hardware and software green-on-brown weed detector that uses entirely off-the-shelf compon
Using a raspberry pi, we listen to the coffee machine and count the number of coffee consumption
A typical datarootsian consumes high-quality fresh coffee in their office environment. The board of dataroots had a very critical decision by the end of 2021-Q2 regarding coffee consumption.
Lightweight Machine Learning Experiment Logging 📖
Simple logging of statistics, model checkpoints, plots and other objects for your Machine Learning Experiments (MLE). Furthermore, the MLELogger comes with smooth multi-seed result aggregation and combination of multi-configuration runs. For a quickstart checkout the notebook blog 🚀
Monitor your ML jobs on mobile devices📱, especially for Google Colab / Kaggle
TF Watcher TF Watcher is a simple to use Python package and web app which allows you to monitor 👀 your Machine Learning training or testing process o
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
Deep learning for spiking neural networks
A deep learning library for spiking neural networks. Norse aims to exploit the advantages of bio-inspired neural components, which are sparse and even
"Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback"
This is code repo for our EMNLP 2017 paper "Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback", which implements the A2C algorithm on top of a neural encoder-decoder model and benchmarks the combination under simulated noisy rewards.
CUDA Python Low-level Bindings
CUDA Python Low-level Bindings
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
QTool: A Low-bit Quantization Toolbox for Deep Neural Networks in Computer Vision
This project provides abundant choices of quantization strategies (such as the quantization algorithms, training schedules and empirical tricks) for quantizing the deep neural networks into low-bit counterparts.
Guesslang detects the programming language of a given source code
Detect the programming language of a source code
pix2tex: Using a ViT to convert images of equations into LaTeX code.
The goal of this project is to create a learning based system that takes an image of a math formula and returns corresponding LaTeX code.
Library for implementing reservoir computing models (echo state networks) for multivariate time series classification and clustering.
Framework overview This library allows to quickly implement different architectures based on Reservoir Computing (the family of approaches popularized
Convert Apple NeuralHash model for CSAM Detection to ONNX.
Apple NeuralHash is a perceptual hashing method for images based on neural networks. It can tolerate image resize and compression.
In this project we investigate the performance of the SetCon model on realistic video footage. Therefore, we implemented the model in PyTorch and tested the model on two example videos.
Contrastive Learning of Object Representations Supervisor: Prof. Dr. Gemma Roig Institutions: Goethe University CVAI - Computational Vision & Artifici
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
LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION
Query Selector Here you can find code and data loaders for the paper https://arxiv.org/pdf/2107.08687v1.pdf . Query Selector is a novel approach to sp
Seeing Dynamic Scene in the Dark: High-Quality Video Dataset with Mechatronic Alignment (ICCV2021)
Seeing Dynamic Scene in the Dark: High-Quality Video Dataset with Mechatronic Alignment This is a pytorch project for the paper Seeing Dynamic Scene i
Learn meanings behind words is a key element in NLP. This project concentrates on the disambiguation of preposition senses. Therefore, we train a bert-transformer model and surpass the state-of-the-art.
New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa
😇A pyTorch implementation of the DeepMoji model: state-of-the-art deep learning model for analyzing sentiment, emotion, sarcasm etc
------ Update September 2018 ------ It's been a year since TorchMoji and DeepMoji were released. We're trying to understand how it's being used such t
IAST: Instance Adaptive Self-training for Unsupervised Domain Adaptation (ECCV 2020)
This repo is the official implementation of our paper "Instance Adaptive Self-training for Unsupervised Domain Adaptation". The purpose of this repo is to better communicate with you and respond to your questions. This repo is almost the same with Another-Version, and you can also refer to that version.
Official code of "R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network."
R2RNet Official code of "R2RNet: Low-light Image Enhancement via Real-low to Real-normal Network." Jiang Hai, Zhu Xuan, Ren Yang, Yutong Hao, Fengzhu
Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+
Based on Yolo's low-power, ultra-lightweight universal target detection algorithm, the parameter is only 250k, and the speed of the smart phone mobile terminal can reach ~300fps+
Large scale embeddings on a single machine.
Marius Marius is a system under active development for training embeddings for large-scale graphs on a single machine. Training on large scale graphs
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l
Sign Language Translation with Transformers (COLING'2020, ECCV'20 SLRTP Workshop)
transformer-slt This repository gathers data and code supporting the experiments in the paper Better Sign Language Translation with STMC-Transformer.
TorchDrug is a PyTorch-based machine learning toolbox designed for drug discovery
A powerful and flexible machine learning platform for drug discovery
nn-Meter is a novel and efficient system to accurately predict the inference latency of DNN models on diverse edge devices
A DNN inference latency prediction toolkit for accurately modeling and predicting the latency on diverse edge devices.
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.
Sum-Product Probabilistic Language
Sum-Product Probabilistic Language SPPL is a probabilistic programming language that delivers exact solutions to a broad range of probabilistic infere
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021
Contrastive Learning for Many-to-many Multilingual Neural Machine Translation(mCOLT/mRASP2), ACL2021 The code for training mCOLT/mRASP2, a multilingua
Production Grade Machine Learning Service
This project is made to help you scale from a basic Machine Learning project for research purposes to a production grade Machine Learning web service
This handbook accompanies the course: Machine Learning with Hung-Yi Lee
This handbook accompanies the course: Machine Learning with Hung-Yi Lee
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.
pydantic-i18n is an extension to support an i18n for the pydantic error messages.
pydantic-i18n is an extension to support an i18n for the pydantic error messages
ThinkTwice: A Two-Stage Method for Long-Text Machine Reading Comprehension
ThinkTwice ThinkTwice is a retriever-reader architecture for solving long-text machine reading comprehension. It is based on the paper: ThinkTwice: A
Machine learning models from Singapore's NLP research community
SG-NLP Machine learning models from Singapore's natural language processing (NLP) research community. sgnlp is a Python package that allows you to eas
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber
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 contains the code for using the H3DS dataset introduced in H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction
H3DS Dataset This repository contains the code for using the H3DS dataset introduced in H3D-Net: Few-Shot High-Fidelity 3D Head Reconstruction Access
Scraping and analysis of leetcode-compensations page.
Leetcode compensations report Scraping and analysis of leetcode-compensations page.
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
Byte-based multilingual transformer TTS for low-resource/few-shot language adaptation.
One model to speak them all 🌎 Audio Language Text ▷ Chinese 人人生而自由,在尊严和权利上一律平等。 ▷ English All human beings are born free and equal in dignity and rig
Punctuation Restoration using Transformer Models for High-and Low-Resource Languages
Punctuation Restoration using Transformer Models This repository contins official implementation of the paper Punctuation Restoration using Transforme
An application that maps an image of a LaTeX math equation to LaTeX code.
Convert images of LaTex math equations into LaTex code.
A PyTorch implementation of Radio Transformer Networks from the paper "An Introduction to Deep Learning for the Physical Layer".
An Introduction to Deep Learning for the Physical Layer An usable PyTorch implementation of the noisy autoencoder infrastructure in the paper "An Intr
🧠 A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation.', ECCV 2016
Deep CORAL A PyTorch implementation of 'Deep CORAL: Correlation Alignment for Deep Domain Adaptation. B Sun, K Saenko, ECCV 2016' Deep CORAL can learn
Xeasy-ml is a packaged machine learning framework.
xeasy-ml 1. What is xeasy-ml Xeasy-ml is a packaged machine learning framework. It allows a beginner to quickly build a machine learning model and use
Universal End2End Training Platform, including pre-training, classification tasks, machine translation, and etc.
背景 安装教程 快速上手 (一)预训练模型 (二)机器翻译 (三)文本分类 TenTrans 进阶 1. 多语言机器翻译 2. 跨语言预训练 背景 TrenTrans是一个统一的端到端的多语言多任务预训练平台,支持多种预训练方式,以及序列生成和自然语言理解任务。 安装教程 git clone git
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.
A collection of interactive machine-learning experiments: 🏋️models training + 🎨models demo
🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo
This is the code repository for Interpretable Machine Learning with Python, published by Packt.
Interpretable Machine Learning with Python, published by Packt
Image Deblurring using Generative Adversarial Networks
DeblurGAN arXiv Paper Version Pytorch implementation of the paper DeblurGAN: Blind Motion Deblurring Using Conditional Adversarial Networks. Our netwo
StarGAN - Official PyTorch Implementation
StarGAN - Official PyTorch Implementation ***** New: StarGAN v2 is available at https://github.com/clovaai/stargan-v2 ***** This repository provides t
PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules
Dynamic Routing Between Capsules - PyTorch implementation PyTorch implementation of NIPS 2017 paper Dynamic Routing Between Capsules from Sara Sabour,
Synthesizing and manipulating 2048x1024 images with conditional GANs
pix2pixHD Project | Youtube | Paper Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic image-to-image translatio
pytorch implementation of Attention is all you need
A Pytorch Implementation of the Transformer: Attention Is All You Need Our implementation is largely based on Tensorflow implementation Requirements N
This's an implementation of deepmind Visual Interaction Networks paper using pytorch
Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch
A PyTorch Implementation of Neural IMage Assessment
NIMA: Neural IMage Assessment This is a PyTorch implementation of the paper NIMA: Neural IMage Assessment (accepted at IEEE Transactions on Image Proc
Dilated RNNs in pytorch
PyTorch Dilated Recurrent Neural Networks PyTorch implementation of Dilated Recurrent Neural Networks (DilatedRNN). Getting Started Installation: $ pi
NIMA: Neural IMage Assessment
PyTorch NIMA: Neural IMage Assessment PyTorch implementation of Neural IMage Assessment by Hossein Talebi and Peyman Milanfar. You can learn more from
PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"
Non-Autoregressive Transformer Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K.
PyTorch implementation of convolutional neural networks-based text-to-speech synthesis models
Deepvoice3_pytorch PyTorch implementation of convolutional networks-based text-to-speech synthesis models: arXiv:1710.07654: Deep Voice 3: Scaling Tex
Code for Emergent Translation in Multi-Agent Communication
Emergent Translation in Multi-Agent Communication PyTorch implementation of the models described in the paper Emergent Translation in Multi-Agent Comm
NLPShala , the best IDE for all Natural language processing tasks.
The revolutionary IDE for all NLP (Natural language processing) stuffs on the internet.
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
TensorFlow Ranking is a library for Learning-to-Rank (LTR) techniques on the TensorFlow platform
Pandas Machine Learning and Quant Finance Library Collection
Pandas Machine Learning and Quant Finance Library Collection
This is an online course where you can learn and master the skill of low-level performance analysis and tuning.
Performance Ninja Class This is an online course where you can learn to find and fix low-level performance issues, for example CPU cache misses and br
T2F: text to face generation using Deep Learning
⭐ [NEW] ⭐ T2F - 2.0 Teaser (coming soon ...) Please note that all the faces in the above samples are generated ones. The T2F 2.0 will be using MSG-GAN
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
CobraML: Completely Customizable A python ML library designed to give the end user full control
CobraML: Completely Customizable What is it? CobraML is a python library built on both numpy and numba. Unlike other ML libraries CobraML gives the us
REST API for sentence tokenization and embedding using Multilingual Universal Sentence Encoder.
MUSE stands for Multilingual Universal Sentence Encoder - multilingual extension (supports 16 languages) of Universal Sentence Encoder (USE).
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
ICML 21 - Voice2Series: Reprogramming Acoustic Models for Time Series Classification
Voice2Series-Reprogramming Voice2Series: Reprogramming Acoustic Models for Time Series Classification International Conference on Machine Learning (IC
[ICML 2021] Towards Understanding and Mitigating Social Biases in Language Models
Towards Understanding and Mitigating Social Biases in Language Models This repo contains code and data for evaluating and mitigating bias from generat
Reference implementation of code generation projects from Facebook AI Research. General toolkit to apply machine learning to code, from dataset creation to model training and evaluation. Comes with pretrained models.
This repository is a toolkit to do machine learning for programming languages. It implements tokenization, dataset preprocessing, model training and m
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
Install alphafold on the local machine, get out of docker.
AlphaFold This package provides an implementation of the inference pipeline of AlphaFold v2.0. This is a completely new model that was entered in CASP
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.
NeuralCompression is a Python repository dedicated to research of neural networks that compress data
NeuralCompression is a Python repository dedicated to research of neural networks that compress data. The repository includes tools such as JAX-based entropy coders, image compression models, video compression models, and metrics for image and video evaluation.
A simple python tool for explore your object detection dataset
A simple tool for explore your object detection dataset. The goal of this library is to provide simple and intuitive visualizations from your dataset and automatically find the best parameters for generating a specific grid of anchors that can fit you data characteristics
Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
vid2vid Project | YouTube(short) | YouTube(full) | arXiv | Paper(full) Pytorch implementation for high-resolution (e.g., 2048x1024) photorealistic vid
PyTorch implementation of "Transparency by Design: Closing the Gap Between Performance and Interpretability in Visual Reasoning"
Transparency-by-Design networks (TbD-nets) This repository contains code for replicating the experiments and visualizations from the paper Transparenc
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
YOLOv3 in PyTorch ONNX CoreML TFLite
This repository represents Ultralytics open-source research into future object detection methods, and incorporates lessons learned and best practices
Pytorch implementation of the DeepDream computer vision algorithm
deep-dream-in-pytorch Pytorch (https://github.com/pytorch/pytorch) implementation of the deep dream (https://en.wikipedia.org/wiki/DeepDream) computer
PyTorch Language Model for 1-Billion Word (LM1B / GBW) Dataset
PyTorch Large-Scale Language Model A Large-Scale PyTorch Language Model trained on the 1-Billion Word (LM1B) / (GBW) dataset Latest Results 39.98 Perp
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
Overview PyTorch 0.4.1 | Python 3.6.5 Annotated implementations with comparative introductions for minimax, non-saturating, wasserstein, wasserstein g
Adversarial Framework for (non-) Parametric Image Stylisation Mosaics
Fully Adversarial Mosaics (FAMOS) Pytorch implementation of the paper "Copy the Old or Paint Anew? An Adversarial Framework for (non-) Parametric Imag
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)
Graph Wavelet Neural Network ⠀⠀ A PyTorch implementation of Graph Wavelet Neural Network (ICLR 2019). Abstract We present graph wavelet neural network
A PyTorch Implementation of "Watch Your Step: Learning Node Embeddings via Graph Attention" (NeurIPS 2018).
Attention Walk ⠀⠀ A PyTorch Implementation of Watch Your Step: Learning Node Embeddings via Graph Attention (NIPS 2018). Abstract Graph embedding meth