6799 Repositories
Python Deep-Learning-for-Text-Document-Classification Libraries
A timer for bird lovers, plays a random birdcall while displaying its image and info.
Birdcall Timer A timer for bird lovers. Siriema hatchling by Junior Peres Junior Background My partner needed a customizable timer for sitting and sta
Python implementation of O-OFDMNet, a deep learning-based optical OFDM system,
O-OFDMNet This includes Python implementation of O-OFDMNet, a deep learning-based optical OFDM system, which uses neural networks for signal processin
A webpage that utilizes machine learning to extract sentiments from tweets.
Tweets_Classification_Webpage The goal of this project is to be able to predict what rating customers on social media platforms would give to products
Unofficial implementation of Google "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization" in PyTorch
CutPaste CutPaste: image from paper Unofficial implementation of Google's "CutPaste: Self-Supervised Learning for Anomaly Detection and Localization"
Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods."
pv_predict_unet-lstm Code for "Intra-hour Photovoltaic Generation Forecasting based on Multi-source Data and Deep Learning Methods." IEEE Transactions
🇰🇷 Text to Image in Korean
KoDALLE Utilizing pretrained language model’s token embedding layer and position embedding layer as DALLE’s text encoder. Background Training DALLE mo
Align and Prompt: Video-and-Language Pre-training with Entity Prompts
ALPRO Align and Prompt: Video-and-Language Pre-training with Entity Prompts [Paper] Dongxu Li, Junnan Li, Hongdong Li, Juan Carlos Niebles, Steven C.H
N-Omniglot is a large neuromorphic few-shot learning dataset
N-Omniglot [Paper] || [Dataset] N-Omniglot is a large neuromorphic few-shot learning dataset. It reconstructs strokes of Omniglot as videos and uses D
Deep Semisupervised Multiview Learning With Increasing Views (IEEE TCYB 2021, PyTorch Code)
Deep Semisupervised Multiview Learning With Increasing Views (ISVN, IEEE TCYB) Peng Hu, Xi Peng, Hongyuan Zhu, Liangli Zhen, Jie Lin, Huaibai Yan, Dez
Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks
The following Python scripts aim to use a Random Forest machine learning algorithm to predict the water affinity of Metal-Organic Frameworks (MOFs). The training set is extracted from the Cambridge Structural Database and the CoRE_MOF 2019 dataset.
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer axriv: http://arxiv.org/abs/2112.13513
MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis This is the official page of the MSHT with its experimental script and records. We de
Official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION.
IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION This is the official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSU
For storing the complete exploration of Visual Question Answering for our B.Tech Project
Multi-Image vqa @authors: Akhilesh, Janhavi, Harsh Paper summary, Ideas tried and their corresponding results: on wiki Other discussions: on discussio
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
Implementation of paper "Self-supervised Learning on Graphs:Deep Insights and New Directions"
SelfTask-GNN A PyTorch implementation of "Self-supervised Learning on Graphs: Deep Insights and New Directions". [paper] In this paper, we first deepe
Source code of the "Graph-Bert: Only Attention is Needed for Learning Graph Representations" paper
Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We
PyTorch code of "SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks"
SLAPS-GNN This repo contains the implementation of the model proposed in SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks
Code for KDD'20 "Generative Pre-Training of Graph Neural Networks"
GPT-GNN: Generative Pre-Training of Graph Neural Networks GPT-GNN is a pre-training framework to initialize GNNs by generative pre-training. It can be
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
Subgraph Based Learning of Contextual Embedding
SLiCE Self-Supervised Learning of Contextual Embeddings for Link Prediction in Heterogeneous Networks Dataset details: We use four public benchmark da
Deeper insights into graph convolutional networks for semi-supervised learning
deeper_insights_into_GCNs Deeper insights into graph convolutional networks for semi-supervised learning References data and utils.py come from Implem
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels"
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt
[ICML 2020] DrRepair: Learning to Repair Programs from Error Messages
DrRepair: Learning to Repair Programs from Error Messages This repo provides the source code & data of our paper: Graph-based, Self-Supervised Program
A Self-Supervised Contrastive Learning Framework for Aspect Detection
AspDecSSCL A Self-Supervised Contrastive Learning Framework for Aspect Detection This repository is a pytorch implementation for the following AAAI'21
Self-Guided Contrastive Learning for BERT Sentence Representations
Self-Guided Contrastive Learning for BERT Sentence Representations This repository is dedicated for releasing the implementation of the models utilize
Autoregressive Predictive Coding: An unsupervised autoregressive model for speech representation learning
Autoregressive Predictive Coding This repository contains the official implementation (in PyTorch) of Autoregressive Predictive Coding (APC) proposed
Self-labelling via simultaneous clustering and representation learning. (ICLR 2020)
Self-labelling via simultaneous clustering and representation learning 🆗 🆗 🎉 NEW models (20th August 2020): Added standard SeLa pretrained torchvis
PyTorch implementation of MoCo: Momentum Contrast for Unsupervised Visual Representation Learning
MoCo: Momentum Contrast for Unsupervised Visual Representation Learning This is a PyTorch implementation of the MoCo paper: @Article{he2019moco, aut
Code for NeurIPS 2020 article "Contrastive learning of global and local features for medical image segmentation with limited annotations"
Contrastive learning of global and local features for medical image segmentation with limited annotations The code is for the article "Contrastive lea
Unsupervised Representation Learning by Invariance Propagation
Unsupervised Learning by Invariance Propagation This repository is the official implementation of Unsupervised Learning by Invariance Propagation. Pre
Official code for the paper "Self-Supervised Prototypical Transfer Learning for Few-Shot Classification"
Self-Supervised Prototypical Transfer Learning for Few-Shot Classification This repository contains the reference source code and pre-trained models (
SCAN: Learning to Classify Images without Labels, incl. SimCLR. [ECCV 2020]
Learning to Classify Images without Labels This repo contains the Pytorch implementation of our paper: SCAN: Learning to Classify Images without Label
Official PyTorch implementation of the paper "Self-Supervised Relational Reasoning for Representation Learning", NeurIPS 2020 Spotlight.
Official PyTorch implementation of the paper: "Self-Supervised Relational Reasoning for Representation Learning" (2020), Patacchiola, M., and Storkey,
Unsupervised Learning of Video Representations using LSTMs
Unsupervised Learning of Video Representations using LSTMs Code for paper Unsupervised Learning of Video Representations using LSTMs by Nitish Srivast
Code and training data for our ECCV 2016 paper on Unsupervised Learning
Shuffle and Learn (Shuffle Tuple) Created by Ishan Misra Based on the ECCV 2016 Paper - "Shuffle and Learn: Unsupervised Learning using Temporal Order
Joint-task Self-supervised Learning for Temporal Correspondence (NeurIPS 2019)
Joint-task Self-supervised Learning for Temporal Correspondence Project | Paper Overview Joint-task Self-supervised Learning for Temporal Corresponden
Official implementation of ACMMM'20 paper 'Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework'
Self-supervised Video Representation Learning Using Inter-intra Contrastive Framework Official code for paper, Self-supervised Video Representation Le
Implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".
PRP Introduction This is the implementation of our paper "Video Playback Rate Perception for Self-supervised Spatio-Temporal Representation Learning".
code for our ECCV-2020 paper: Self-supervised Video Representation Learning by Pace Prediction
Video_Pace This repository contains the code for the following paper: Jiangliu Wang, Jianbo Jiao and Yunhui Liu, "Self-Supervised Video Representation
Video Representation Learning by Recognizing Temporal Transformations. In ECCV, 2020.
Video Representation Learning by Recognizing Temporal Transformations [Project Page] Simon Jenni, Givi Meishvili, and Paolo Favaro. In ECCV, 2020. Thi
[NeurIPS'20] Self-supervised Co-Training for Video Representation Learning. Tengda Han, Weidi Xie, Andrew Zisserman.
CoCLR: Self-supervised Co-Training for Video Representation Learning This repository contains the implementation of: InfoNCE (MoCo on videos) UberNCE
[arXiv 2020] Video Representation Learning with Visual Tempo Consistency
Video Representation Learning with Visual Tempo Consistency [Paper] [Project Page] News Full codebae is coming soon Pretained Models For now, we provi
Official Pytorch implementation for AAAI2021 paper (RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning)
RSPNet Official Pytorch implementation for AAAI2021 paper "RSPNet: Relative Speed Perception for Unsupervised Video Representation Learning" [Suppleme
Code for Paper: Self-supervised Learning of Motion Capture
Self-supervised Learning of Motion Capture This is code for the paper: Hsiao-Yu Fish Tung, Hsiao-Wei Tung, Ersin Yumer, Katerina Fragkiadaki, Self-sup
An unsupervised learning framework for depth and ego-motion estimation from monocular videos
SfMLearner This codebase implements the system described in the paper: Unsupervised Learning of Depth and Ego-Motion from Video Tinghui Zhou, Matthew
Geometry-Aware Learning of Maps for Camera Localization (CVPR2018)
Geometry-Aware Learning of Maps for Camera Localization This is the PyTorch implementation of our CVPR 2018 paper "Geometry-Aware Learning of Maps for
Codebase for ECCV18 "The Sound of Pixels"
Sound-of-Pixels Codebase for ECCV18 "The Sound of Pixels". *This repository is under construction, but the core parts are already there. Environment T
Code for "Unsupervised State Representation Learning in Atari"
Unsupervised State Representation Learning in Atari Ankesh Anand*, Evan Racah*, Sherjil Ozair*, Yoshua Bengio, Marc-Alexandre Côté, R Devon Hjelm This
Artificial intelligence technology inferring issues and logically supporting facts from raw text
개요 비정형 텍스트를 학습하여 쟁점별 사실과 논리적 근거 추론이 가능한 인공지능 원천기술 Artificial intelligence techno
Deep Learning Training Scripts With Python
Deep Learning Training Scripts DNN Frameworks Caffe PyTorch Tensorflow CNN Models VGG ResNet DenseNet Inception Language Modeling GatedCNN-LM Attentio
This is a Python program that implements a vacuum cleaner as an Artificial Intelligence.
Vacuum-Cleaner Python3 This is a Python3 agent that implements a simulator for a vacuum cleaner and it is introduction to Artificial Intelligence. A s
A tool combining EasyOCR and LaMa to automatically detect text and replace it with an inpainted background.
EasyLaMa (WIP) This is a tool combining EasyOCR and LaMa to automatically detect text and replace it with an inpainted background. Installation For GP
Pytorch implementation of the AAAI 2022 paper "Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification"
[AAAI22] Cross-Domain Empirical Risk Minimization for Unbiased Long-tailed Classification We point out the overlooked unbiasedness in long-tailed clas
Scene-Text-Detection-and-Recognition (Pytorch)
Scene-Text-Detection-and-Recognition (Pytorch) Competition URL: https://tbrain.t
Official repository of the paper Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
Official repository of the paper Learning to Regress 3D Face Shape and Expression from an Image without 3D Supervision
Transformation spoken text to written text
Transformation spoken text to written text This model is used for formatting raw asr text output from spoken text to written text (Eg. date, number, i
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis
HiFi-GAN: Generative Adversarial Networks for Efficient and High Fidelity Speech Synthesis Jungil Kong, Jaehyeon Kim, Jaekyoung Bae In our paper, we p
Indonesian Car License Plate Character Recognition using Tensorflow, Keras and OpenCV.
Monopol Indonesian Car License Plate (Indonesia Mobil Nomor Polisi) Character Recognition using Tensorflow, Keras and OpenCV. Background This applicat
nlpcommon is a python Open Source Toolkit for text classification.
nlpcommon nlpcommon, Python Text Tool. Guide Feature Install Usage Dataset Contact Cite Reference Feature nlpcommon is a python Open Source
🚀Clone a voice in 5 seconds to generate arbitrary speech in real-time
English | 中文 Features 🌍 Chinese supported mandarin and tested with multiple datasets: aidatatang_200zh, magicdata, aishell3, data_aishell, and etc. ?
Extract city and country mentions from Text like GeoText without regex, but FlashText, a Aho-Corasick implementation.
flashgeotext ⚡ 🌍 Extract and count countries and cities (+their synonyms) from text, like GeoText on steroids using FlashText, a Aho-Corasick impleme
whylogs: A Data and Machine Learning Logging Standard
whylogs: A Data and Machine Learning Logging Standard whylogs is an open source standard for data and ML logging whylogs logging agent is the easiest
OpenAI CLIP text encoders for multiple languages!
Multilingual-CLIP OpenAI CLIP text encoders for any language Colab Notebook · Pre-trained Models · Report Bug Overview OpenAI recently released the pa
txtai: Build AI-powered semantic search applications in Go
txtai: Build AI-powered semantic search applications in Go txtai executes machine-learning workflows to transform data and build AI-powered semantic s
A deep learning model for style-specific music generation.
DeepJ: A model for style-specific music generation https://arxiv.org/abs/1801.00887 Abstract Recent advances in deep neural networks have enabled algo
Fast, DB Backed pretrained word embeddings for natural language processing.
Embeddings Embeddings is a python package that provides pretrained word embeddings for natural language processing and machine learning. Instead of lo
Multilingual word vectors in 78 languages
Aligning the fastText vectors of 78 languages Facebook recently open-sourced word vectors in 89 languages. However these vectors are monolingual; mean
PyTorch Implementation for Deep Metric Learning Pipelines
Easily Extendable Basic Deep Metric Learning Pipeline Karsten Roth ([email protected]), Biagio Brattoli ([email protected]) When using thi
The easiest way to use deep metric learning in your application. Modular, flexible, and extensible. Written in PyTorch.
News December 27: v1.1.0 New loss functions: CentroidTripletLoss and VICRegLoss Mean reciprocal rank + per-class accuracies See the release notes Than
Template repository to build PyTorch projects from source on any version of PyTorch/CUDA/cuDNN.
The Ultimate PyTorch Source-Build Template Translations: 한국어 TL;DR PyTorch built from source can be x4 faster than a naïve PyTorch install. This repos
Final project for machine learning (CSC 590). Detection of hepatitis C and progression through blood samples.
Hepatitis C Blood Based Detection Final project for machine learning (CSC 590). Dataset from Kaggle. Using data from previous hepatitis C blood panels
This is a telegram bot help you to get stylish fonts and text.
Stylish Font Bot 🐿 This is a telegram bot help you to get stylish fonts and text. Deploy to heroku 🗳 Press the button Deploy to heroku and give the
Retrieve annotated intron sequences and classify them as minor (U12-type) or major (U2-type)
(intron I nterrogator and C lassifier) intronIC is a program that can be used to classify intron sequences as minor (U12-type) or major (U2-type), usi
A curated list of the latest breakthroughs in AI (in 2021) by release date with a clear video explanation, link to a more in-depth article, and code.
2021: A Year Full of Amazing AI papers- A Review 📌 A curated list of the latest breakthroughs in AI by release date with a clear video explanation, l
Adventura is an open source Python Text Adventure Engine
Adventura Adventura is an open source Python Text Adventure Engine, Not yet uplo
Medical-Image-Triage-and-Classification-System-Based-on-COVID-19-CT-and-X-ray-Scan-Dataset
Medical-Image-Triage-and-Classification-System-Based-on-COVID-19-CT-and-X-ray-Sc
Learning and experimenting with Kubernetes
Kubernetes Experiments This repository contains code that I'm using to learn and experiment with Kubernetes. 1. Environment setup minikube kubectl doc
All-in-one web-based development environment for machine learning
All-in-one web-based development environment for machine learning Getting Started • Features & Screenshots • Support • Report a Bug • FAQ • Known Issu
Python Moonlight (Machine Learning) Practice
PyML Python Moonlight (Machine Learning) Practice Contents Design Documentation Prerequisites Checklist Dev Setup Testing Run Prerequisites Python 3 P
API to summarize input text
summaries API to summarize input text normal run $ docker-compose exec web python -m pytest disable warnings $ docker-compose exec web python -m pytes
Online learning platform
🛠 Status: In Development Teached is currently in development. So we encourage you to use it and give us your feedback, but there are things that have
Implementation of Memory-Efficient Neural Networks with Multi-Level Generation, ICCV 2021
Memory-Efficient Multi-Level In-Situ Generation (MLG) By Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen and David Z. Pan
Machine Learning Course Project, IMDB movie review sentiment analysis by lstm, cnn, and transformer
IMDB Sentiment Analysis This is the final project of Machine Learning Courses in Huazhong University of Science and Technology, School of Artificial I
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size.
Hub is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. The hub data layout enables rapid transformations and streaming of data while training models at scale. Hub is used by Google, Waymo, Red Cross, Oxford University, and Omdena.
LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code.
LazyText is inspired b the idea of lazypredict, a library which helps build a lot of basic models without much code. LazyText is for text what lazypredict is for numeric data.
Terminal Colored Text for Python
Terminal Colored Text for Python
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels
Simple and Robust Loss Design for Multi-Label Learning with Missing Labels Official PyTorch Implementation of the paper Simple and Robust Loss Design
Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2021)
Applied Machine Learning (Cornell CS5785, Fall 2021) This repo contains executable course notes and slides for the Applied ML course at Cornell and Co
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning Yansong Tang *, Zhenyu Jiang *, Zhenda Xie *, Yue
An Instagram bot that can mass text users, receive and read a text, and store it somewhere with user details.
Instagram Bot 🤖 July 14, 2021 Overview 👍 A multifunctionality automated instagram bot that can mass text users, receive and read a message and store
A module for parsing and processing commands.
cmdtools A module for parsing and processing commands. Installation pip install --upgrade cmdtools-py install latest commit from GitHub pip install g
Learning hierarchical attention for weakly-supervised chest X-ray abnormality localization and diagnosis
Hierarchical Attention Mining (HAM) for weakly-supervised abnormality localization This is the official PyTorch implementation for the HAM method. Pap
Um RPG de texto orientado a objetos.
RPG de texto Um RPG de texto orientado a objetos, sem história. Um RPG (Role-playing game) baseado em texto em que você pode viajar para alguns locais
An extreme encryption for everyone, encrypt your text before sending to anyone.
An extreme encryption for everyone, encrypt your text before sending to anyone. Alphabets and numbers are going to be encrypted like a hell
Example GUI for Command line capable machine learning programs
Example GUI for Command line capable machine learning programs This is an example GUI made in PysimpleGUI and Tkinter, mainly for machine learning pro
Pytorch based library to rank predicted bounding boxes using text/image user's prompts.
pytorch_clip_bbox: Implementation of the CLIP guided bbox ranking for Object Detection. Pytorch based library to rank predicted bounding boxes using t
A repository to index and organize the latest machine learning courses found on YouTube.
📺 ML YouTube Courses At DAIR.AI we ❤️ open education. We are excited to share some of the best and most recent machine learning courses available on
ONNX Command-Line Toolbox
ONNX Command Line Toolbox Aims to improve your experience of investigating ONNX models. Use it like onnx infershape /path/to/model.onnx. (See the usag
A lightweight tool to get an AI Infrastructure Stack up in minutes not days.
K3ai will take care of setup K8s for You, deploy the AI tool of your choice and even run your code on it.