6252 Repositories
Python Lighting-the-Darkness-in-the-Deep-Learning-Era-Open Libraries
AWS documentation corpus for zero-shot open-book question answering.
aws-documentation We present the AWS documentation corpus, an open-book QA dataset, which contains 25,175 documents along with 100 matched questions a
Machine Learning Framework for Operating Systems - Brings ML to Linux kernel
KML: A Machine Learning Framework for Operating Systems & Storage Systems Storage systems and their OS components are designed to accommodate a wide v
Semi-Supervised Learning for Fine-Grained Classification
Semi-Supervised Learning for Fine-Grained Classification This repo contains the code of: A Realistic Evaluation of Semi-Supervised Learning for Fine-G
Self-Regulated Learning for Egocentric Video Activity Anticipation
Self-Regulated Learning for Egocentric Video Activity Anticipation Introduction This is a Pytorch implementation of the model described in our paper:
ChebLieNet, a spectral graph neural network turned equivariant by Riemannian geometry on Lie groups.
ChebLieNet: Invariant spectral graph NNs turned equivariant by Riemannian geometry on Lie groups Hugo Aguettaz, Erik J. Bekkers, Michaël Defferrard We
The code for 'Deep Residual Fourier Transformation for Single Image Deblurring'
Deep Residual Fourier Transformation for Single Image Deblurring Xintian Mao, Yiming Liu, Wei Shen, Qingli Li and Yan Wang code will be released soon
EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation (CVPR'21)
EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation (CVPR'21) Citation If y
Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Neural Networks.
Dynamic-Graphs-Construction Official Codes for Graph Modularity:Towards Understanding the Cross-Layer Transition of Feature Representations in Deep Ne
Code for testing convergence rates of Lipschitz learning on graphs
📈 LipschitzLearningRates The code in this repository reproduces the experimental results on convergence rates for k-nearest neighbor graph infinity L
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes
Lepard: Learning Partial point cloud matching in Rigid and Deformable scenes [Paper] Method overview 4DMatch Benchmark 4DMatch is a benchmark for matc
This is the official PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks This is the official repository for our paper: Sharpness-aware Quantization for Deep Neural Netw
This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression problems
Doctoral dissertation of Zheng Zhao This thesis is mainly concerned with state-space methods for a class of deep Gaussian process (DGP) regression pro
Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling".
PSSL Source code of CIKM2021 Long Paper "PSSL: Self-supervised Learning for Personalized Search with Contrastive Sampling". It consists of the pre-tra
Reproduced Code for Image Forgery Detection papers.
Image Forgery Detection With over 4.5 billion active internet users, the amount of multimedia content being shared every day has surpassed everyone’s
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Introduction English | 简体ä¸æ–‡ MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the correspondi
OpenMMLab Image Classification Toolbox and Benchmark
Introduction English | 简体ä¸æ–‡ MMClassification is an open source image classification toolbox based on PyTorch. It is a part of the OpenMMLab project. D
Jittor is a high-performance deep learning framework based on JIT compiling and meta-operators.
Jittor: a Just-in-time(JIT) deep learning framework Quickstart | Install | Tutorial | Chinese Jittor is a high-performance deep learning framework bas
A minimal solution to hand motion capture from a single color camera at over 100fps. Easy to use, plug to run.
Minimal Hand A minimal solution to hand motion capture from a single color camera at over 100fps. Easy to use, plug to run. This project provides the
Code release for Local Light Field Fusion at SIGGRAPH 2019
Local Light Field Fusion Project | Video | Paper Tensorflow implementation for novel view synthesis from sparse input images. Local Light Field Fusion
A colab notebook for training Stylegan2-ada on colab, transfer learning onto your own dataset.
Stylegan2-Ada-Google-Colab-Starter-Notebook A no thrills colab notebook for training Stylegan2-ada on colab. transfer learning onto your own dataset h
YOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
Yolo v4, v3 and v2 for Windows and Linux (neural networks for object detection) Paper YOLO v4: https://arxiv.org/abs/2004.10934 Paper Scaled YOLO v4:
🧪 Cutting-edge experimental spaCy components and features
spacy-experimental: Cutting-edge experimental spaCy components and features This package includes experimental components and features for spaCy v3.x,
Anytime Learning At Macroscale
On Anytime Learning At Macroscale Learning from sequential data dumps (key) Requirements Python 3.7 Pytorch 1.9.0 Hydra 1.1.0 (pip install hydra-core
Code for DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning
DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive Learning Pytorch Implementation for DisCo: Remedy Self-supervi
A hybrid SOTA solution of LiDAR panoptic segmentation with C++ implementations of point cloud clustering algorithms. ICCV21, Workshop on Traditional Computer Vision in the Age of Deep Learning
ICCVW21-TradiCV-Survey-of-LiDAR-Cluster Motivation In contrast to popular end-to-end deep learning LiDAR panoptic segmentation solutions, we propose a
Learning Logic Rules for Document-Level Relation Extraction
LogiRE Learning Logic Rules for Document-Level Relation Extraction We propose to introduce logic rules to tackle the challenges of doc-level RE. Equip
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati
An implementation for the ICCV 2021 paper Deep Permutation Equivariant Structure from Motion.
Deep Permutation Equivariant Structure from Motion Paper | Poster This repository contains an implementation for the ICCV 2021 paper Deep Permutation
Official Pytorch implementation of "DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network" (CVPR'21)
DivCo: Diverse Conditional Image Synthesis via Contrastive Generative Adversarial Network Pytorch implementation for our DivCo. We propose a simple ye
Repo for our ICML21 paper Unsupervised Learning of Visual 3D Keypoints for Control
Unsupervised Learning of Visual 3D Keypoints for Control [Project Website] [Paper] Boyuan Chen1, Pieter Abbeel1, Deepak Pathak2 1UC Berkeley 2Carnegie
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
MeTAL - Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning (ICCV2021 Oral) Sungyong Baik, Janghoon Choi, Heewon Kim, Dohee Cho, Jaes
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Repository of best practices for deep learning in Julia, inspired by fastai
FastAI Docs: Stable | Dev FastAI.jl is inspired by fastai, and is a repository of best practices for deep learning in Julia. Its goal is to easily ena
The fastai book, published as Jupyter Notebooks
English / Spanish / Korean / Chinese / Bengali / Indonesian The fastai book These notebooks cover an introduction to deep learning, fastai, and PyTorc
Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks.
Self Supervised Learning with Fastai Implementation of popular SOTA self-supervised learning algorithms as Fastai Callbacks. Install pip install self-
🔊 Audio and fastai v2
Fastaudio An audio module for fastai v2. We want to help you build audio machine learning applications while minimizing the need for audio domain expe
Walk with fastai
Shield: This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. Walk with fastai What is this p
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.
Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models
An Agnostic Computer Vision Framework - Pluggable to any Training Library: Fastai, Pytorch-Lightning with more to come
An Agnostic Object Detection Framework IceVision is the first agnostic computer vision framework to offer a curated collection with hundreds of high-q
Fast style transfer
faststyle Faststyle aims to provide an easy and modular interface to Image to Image problems based on feature loss. Install Making sure you have a wor
A fastai/PyTorch package for unpaired image-to-image translation.
Unpaired image-to-image translation A fastai/PyTorch package for unpaired image-to-image translation currently with CycleGAN implementation. This is a
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
Compare MLOps Platforms. Breakdowns of SageMaker, VertexAI, AzureML, Dataiku, Databricks, h2o, kubeflow, mlflow...
A modular domain adaptation library written in PyTorch.
A modular domain adaptation library written in PyTorch.
Deep Reinforced Attention Regression for Partial Sketch Based Image Retrieval.
DARP-SBIR Intro This repository contains the source code implementation for ICDM submission paper Deep Reinforced Attention Regression for Partial Ske
Domain Generalization for Mammography Detection via Multi-style and Multi-view Contrastive Learning
MSVCL_MICCAI2021 Installation Please follow the instruction in pytorch-CycleGAN-and-pix2pix to install. Example Usage An example of vendor-styles tran
Official Implementation of "Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras"
Multi Camera Pig Tracking Official Implementation of Tracking Grow-Finish Pigs Across Large Pens Using Multiple Cameras CVPR2021 CV4Animals Workshop P
The Most Efficient Temporal Difference Learning Framework for 2048
moporgic/TDL2048+ TDL2048+ is a highly optimized temporal difference (TD) learning framework for 2048. Features Many common methods related to 2048 ar
MLJetReconstruction - using machine learning to reconstruct jets for CMS
MLJetReconstruction - using machine learning to reconstruct jets for CMS The C++ data extraction code used here was based heavily on that foundv here.
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks
FedCV: A Federated Learning Framework for Diverse Computer Vision Tasks Image Classification Dataset: Google Landmark, COCO, ImageNet Model: Efficient
Curating a dataset for bioimage transfer learning
CytoImageNet A large-scale pretraining dataset for bioimage transfer learning. Motivation In past few decades, the increase in speed of data collectio
cleanlab is the data-centric ML ops package for machine learning with noisy labels.
cleanlab is the data-centric ML ops package for machine learning with noisy labels. cleanlab cleans labels and supports finding, quantifying, and lear
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis.
Kaggler is a Python package for lightweight online machine learning algorithms and utility functions for ETL and data analysis. It is distributed under the MIT License.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas.
Skoot is a lightweight python library of machine learning transformer classes that interact with scikit-learn and pandas. Its objective is to ex
dirty_cat is a Python module for machine-learning on dirty categorical variables.
dirty_cat dirty_cat is a Python module for machine-learning on dirty categorical variables.
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models.
Feature-engine is a Python library with multiple transformers to engineer and select features for use in machine learning models. Feature-engine's transformers follow scikit-learn's functionality with fit() and transform() methods to first learn the transforming parameters from data and then transform the data.
Open-source python package for the extraction of Radiomics features from 2D and 3D images and binary masks.
pyradiomics v3.0.1 Build Status Linux macOS Windows Radiomics feature extraction in Python This is an open-source python package for the extraction of
A Guide for Feature Engineering and Feature Selection, with implementations and examples in Python.
Feature Engineering & Feature Selection A comprehensive guide [pdf] [markdown] for Feature Engineering and Feature Selection, with implementations and
stability-selection - A scikit-learn compatible implementation of stability selection
stability-selection - A scikit-learn compatible implementation of stability selection stability-selection is a Python implementation of the stability
apricot implements submodular optimization for the purpose of selecting subsets of massive data sets to train machine learning models quickly.
Please consider citing the manuscript if you use apricot in your academic work! You can find more thorough documentation here. apricot implements subm
A Domain-Agnostic Benchmark for Self-Supervised Learning
DABS: A Domain Agnostic Benchmark for Self-Supervised Learning This repository contains the code for DABS, a benchmark for domain-agnostic self-superv
PyTorch implementation for "Sharpness-aware Quantization for Deep Neural Networks".
Sharpness-aware Quantization for Deep Neural Networks Recent Update 2021.11.23: We release the source code of SAQ. Setup the environments Clone the re
Open Source Discord Account Creator
Alter Token Generator Open Source Discord Account Creator This program abuses the discord api and uses the 2Captcha captcha solving service to make di
Weakly Supervised Dense Event Captioning in Videos, i.e. generating multiple sentence descriptions for a video in a weakly-supervised manner.
WSDEC This is the official repo for our NeurIPS paper Weakly Supervised Dense Event Captioning in Videos. Description Repo directories ./: global conf
VR-Caps: A Virtual Environment for Active Capsule Endoscopy
VR-Caps: A Virtual Environment for Capsule Endoscopy Overview We introduce a virtual active capsule endoscopy environment developed in Unity that prov
Deep and online learning with spiking neural networks in Python
Introduction The brain is the perfect place to look for inspiration to develop more efficient neural networks. One of the main differences with modern
Universal Probability Distributions with Optimal Transport and Convex Optimization
Sylvester normalizing flows for variational inference Pytorch implementation of Sylvester normalizing flows, based on our paper: Sylvester normalizing
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models. Hyperactive: is very easy to lear
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition, CVPR 2018
PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place Recognition PointNetVLAD: Deep Point Cloud Based Retrieval for Large-Scale Place
Tensorboard for pytorch (and chainer, mxnet, numpy, ...)
tensorboardX Write TensorBoard events with simple function call. The current release (v2.3) is tested on anaconda3, with PyTorch 1.8.1 / torchvision 0
Current state of supervised and unsupervised depth completion methods
Awesome Depth Completion Table of Contents About Sparse-to-Dense Depth Completion Current State of Depth Completion Unsupervised VOID Benchmark Superv
Katana project is a template for ASAP 🚀 ML application deployment
Katana project is a FastAPI template for ASAP 🚀 ML API deployment
Discovering Interpretable GAN Controls [NeurIPS 2020]
GANSpace: Discovering Interpretable GAN Controls Figure 1: Sequences of image edits performed using control discovered with our method, applied to thr
A high-performance topological machine learning toolbox in Python
giotto-tda is a high-performance topological machine learning toolbox in Python built on top of scikit-learn and is distributed under the G
Single-Cell Analysis in Python. Scales to 1M cells.
Scanpy – Single-Cell Analysis in Python Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It inc
Live training loss plot in Jupyter Notebook for Keras, PyTorch and others
livelossplot Don't train deep learning models blindfolded! Be impatient and look at each epoch of your training! (RECENT CHANGES, EXAMPLES IN COLAB, A
A Bokeh project developed for learning and teaching Bokeh interactive plotting!
Bokeh-Python-Visualization A Bokeh project developed for learning and teaching Bokeh interactive plotting! See my medium blog posts about making bokeh
Streamlit — The fastest way to build data apps in Python
Welcome to Streamlit 👋 The fastest way to build and share data apps. Streamlit lets you turn data scripts into sharable web apps in minutes, not week
The purpose of this project is to share knowledge on how awesome Streamlit is and can be
Awesome Streamlit The fastest way to build Awesome Tools and Apps! Powered by Python! The purpose of this project is to share knowledge on how Awesome
PyCaret is an open-source, low-code machine learning library in Python that automates machine learning workflows.
An open-source, low-code machine learning library in Python 🚀 Version 2.3.5 out now! Check out the release notes here. Official • Docs • Install • Tu
Scikit-Garden or skgarden is a garden for Scikit-Learn compatible decision trees and forests.
Scikit-Garden or skgarden (pronounced as skarden) is a garden for Scikit-Learn compatible decision trees and forests.
InfiniteBoost: building infinite ensembles with gradient descent
InfiniteBoost Code for a paper InfiniteBoost: building infinite ensembles with gradient descent (arXiv:1706.01109). A. Rogozhnikov, T. Likhomanenko De
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
🌲 Implementation of the Robust Random Cut Forest algorithm for anomaly detection on streams
A fast, efficient universal vector embedding utility package.
Magnitude: a fast, simple vector embedding utility library A feature-packed Python package and vector storage file format for utilizing vector embeddi
ETNA – time series forecasting framework
ETNA Time Series Library Predict your time series the easiest way Homepage | Documentation | Tutorials | Contribution Guide | Release Notes ETNA is an
mmfewshot is an open source few shot learning toolbox based on PyTorch
OpenMMLab FewShot Learning Toolbox and Benchmark
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
A method that utilized Generative Adversarial Network (GAN) to interpret the black-box deep image classifier models by PyTorch.
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)
To run the code Unzip the package to your local directory; Run 'pip install -r requirements.txt' to download required packages; Open file ~/nips_code/
Python module for data science and machine learning users.
dsnk-distributions package dsnk distribution is a Python module for data science and machine learning that was created with the goal of reducing calcu
🔎 Most Advanced Open Source Intelligence (OSINT) Framework for scanning IP Address, Emails, Websites, Organizations.
🔎 Most Advanced Open Source Intelligence (OSINT) Framework for scanning IP Address, Emails, Websites, Organizations.
A Powerful Serverless Analysis Toolkit That Takes Trial And Error Out of Machine Learning Projects
KXY: A Seemless API to 10x The Productivity of Machine Learning Engineers Documentation https://www.kxy.ai/reference/ Installation From PyPi: pip inst
Detectron2 for Document Layout Analysis
Detectron2 trained on PubLayNet dataset This repo contains the training configurations, code and trained models trained on PubLayNet dataset using Det
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models.
Backprop makes it simple to use, finetune, and deploy state-of-the-art ML models. Solve a variety of tasks with pre-trained models or finetune them in
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open
Naszilla is a Python library for neural architecture search (NAS)
A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow
Fisherman is a free open source fishing bot written in python.
Fisherman is a free open source fishing bot written in python.
[AAAI2021] The source code for our paper 《Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion》.
DSM The source code for paper Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion Project Website; Datasets li
An Active Automata Learning Library Written in Python
AALpy An Active Automata Learning Library AALpy is a light-weight active automata learning library written in pure Python. You can start learning auto
ClearML - Auto-Magical Suite of tools to streamline your ML workflow. Experiment Manager, MLOps and Data-Management
ClearML - Auto-Magical Suite of tools to streamline your ML workflow Experiment Manager, MLOps and Data-Management ClearML Formerly known as Allegro T
Neural networks applied in recognizing guitar chords using python, AutoML.NET with C# and .NET Core
Chord Recognition Demo application The demo application is written in C# with .NETCore. As of July 9, 2020, the only version available is for windows