7480 Repositories
Python play-daxigua-using-Reinforcement-Learning Libraries
BudouX is the successor to Budou, the machine learning powered line break organizer tool.
BudouX Standalone. Small. Language-neutral. BudouX is the successor to Budou, the machine learning powered line break organizer tool. It is standalone
GUI for TOAD-GAN, a PCG-ML algorithm for Token-based Super Mario Bros. Levels.
If you are using this code in your own project, please cite our paper: @inproceedings{awiszus2020toadgan, title={TOAD-GAN: Coherent Style Level Gene
Using this codebase as a tool for my own research. Making some modifications to the original repo for my own purposes.
For SwapNet Create a list.txt file containing all the images to process. This can be done with the GNU find command: find path/to/input/folder -name '
Usable Implementation of "Bootstrap Your Own Latent" self-supervised learning, from Deepmind, in Pytorch
Bootstrap Your Own Latent (BYOL), in Pytorch Practical implementation of an astoundingly simple method for self-supervised learning that achieves a ne
Softlearning is a reinforcement learning framework for training maximum entropy policies in continuous domains. Includes the official implementation of the Soft Actor-Critic algorithm.
Softlearning Softlearning is a deep reinforcement learning toolbox for training maximum entropy policies in continuous domains. The implementation is
Keyword spotting on Arm Cortex-M Microcontrollers
Keyword spotting for Microcontrollers This repository consists of the tensorflow models and training scripts used in the paper: Hello Edge: Keyword sp
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.
Extensions for using Rich with Django.
django-rich Extensions for using Rich with Django. Requirements Python 3.6 to 3.10 supported. Django 2.2 to 4.0 supported. Are your tests slow? Check
Set of classes and tools to communicate with a Noso wallet using NosoP
NosoPy Set of classes and tools to communicate with a Noso wallet using NosoP(Noso Protocol). The data that can be retrieved consist of: Node informat
A simple script written using symbolic python that takes as input a desired metric and automatically calculates and outputs the Christoffel Pseudo-Tensor, Riemann Curvature Tensor, Ricci Tensor, Scalar Curvature and the Kretschmann Scalar
A simple script written using symbolic python that takes as input a desired metric and automatically calculates and outputs the Christoffel Pseudo-Tensor, Riemann Curvature Tensor, Ricci Tensor, Scalar Curvature and the Kretschmann Scalar
Test for using pyIIIFpres for rara magnetica project
raramagnetica_pyIIIFpres Test for using pyIIIFpres for rara magnetica project. This test show how to use pyIIIFpres for creating mannifest compliant t
Source code for CVPR 2020 paper "Learning to Forget for Meta-Learning"
L2F - Learning to Forget for Meta-Learning Sungyong Baik, Seokil Hong, Kyoung Mu Lee Source code for CVPR 2020 paper "Learning to Forget for Meta-Lear
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
AdderNet: Do We Really Need Multiplications in Deep Learning? This code is a demo of CVPR 2020 paper AdderNet: Do We Really Need Multiplications in De
Learning Continuous Signed Distance Functions for Shape Representation
DeepSDF This is an implementation of the CVPR '19 paper "DeepSDF: Learning Continuous Signed Distance Functions for Shape Representation" by Park et a
Training code and evaluation benchmarks for the "Self-Supervised Policy Adaptation during Deployment" paper.
Self-Supervised Policy Adaptation during Deployment PyTorch implementation of PAD and evaluation benchmarks from Self-Supervised Policy Adaptation dur
Learning Correspondence from the Cycle-consistency of Time (CVPR 2019)
TimeCycle Code for Learning Correspondence from the Cycle-consistency of Time (CVPR 2019, Oral). The code is developed based on the PyTorch framework,
Awesome Deep Graph Clustering is a collection of SOTA, novel deep graph clustering methods
ADGC: Awesome Deep Graph Clustering ADGC is a collection of state-of-the-art (SOTA), novel deep graph clustering methods (papers, codes and datasets).
Code for Active Learning at The ImageNet Scale.
Code for Active Learning at The ImageNet Scale. This repository implements many popular active learning algorithms and allows training with torch's DDP.
TeST: Temporal-Stable Thresholding for Semi-supervised Learning
TeST: Temporal-Stable Thresholding for Semi-supervised Learning TeST Illustration Semi-supervised learning (SSL) offers an effective method for large-
Yaml - Loggers are like print() statements
Upgrade your print statements Loggers are like print() statements except they also include loads of other metadata: timestamp msg (same as print!) arg
Xanadu Quantum Codebook is an experimental, exercise-based introduction to quantum computing using PennyLane.
Xanadu Quantum Codebook The Xanadu Quantum Codebook is an experimental, exercise-based introduction to quantum computing using PennyLane. This reposit
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
RecList is an open source library providing behavioral, "black-box" testing for recommender systems.
PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems
PowerGridworld provides users with a lightweight, modular, and customizable framework for creating power-systems-focused, multi-agent Gym environments that readily integrate with existing training frameworks for reinforcement learning (RL).
Source files for the data lake demo video using the AWS TICKIT database
Data Lake Demo Source code for video demonstration detailed in the post, Building a Simple Data Lake on AWS . Build a simple data lake on AWS using a
Automated question generation and question answering from Turkish texts using text-to-text transformers
Turkish Question Generation Offical source code for "Automated question generation & question answering from Turkish texts using text-to-text transfor
Multi-Agent Reinforcement Learning (MARL) method to learn scalable control polices for multi-agent target tracking.
scalableMARL Scalable Reinforcement Learning Policies for Multi-Agent Control CD. Hsu, H. Jeong, GJ. Pappas, P. Chaudhari. "Scalable Reinforcement Lea
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021
Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021 Abstract Recent works have made great success in semantic segmentation by explo
A tool to enhance your old/damaged pictures built using python & opencv.
Breathe Life into your Old Pictures Table of Contents About The Project Getting Started Prerequisites Usage Contact Acknowledgments About The Project
Code for Paper Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning
Predicting Osteoarthritis Progression via Unsupervised Adversarial Representation Learning (c) Tianyu Han and Daniel Truhn, RWTH Aachen University, 20
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
Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes
Using Language Model to Bootstrap Human Activity Recognition Ambient Sensors Based in Smart Homes This repository is the official implementation of Us
Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks
Hidden-Fold Networks (HFN): Random Recurrent Residuals Using Sparse Supermasks by Ángel López García-Arias, Masanori Hashimoto, Masato Motomura, and J
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
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 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
Code Generation using a large neural network called GPT-J
CodeGenX is a Code Generation system powered by Artificial Intelligence! It is delivered to you in the form of a Visual Studio Code Extension and is Free and Open-source!
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Introduction English | 简体中文 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 | 简体中文 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
Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data.
Web scraped S&P 500 Data from Wikipedia using Pandas and performed Exploratory Data Analysis on the data. Then used Yahoo Finance to get the related stock data and displayed them in the form of charts.
School Project using Python Sockets and Personal Encryption Method.
Python-Secure-File-Transfer School Project using Python Sockets and Personal Encryption Method. Installation Must have python3 installed on your syste
A naive Bayes model for cancer classification using a set of documents
Naivebayes text classifcation model for cancer and noncancer documents Author: Alex King Purpose Requirements/files included How to use 1. Purpose The
A Discord Bot that tracks and displays cryptocurrencies using the CoinMarketCap API
PyBo - A Crypto Inspired Discord Bot Pybo (paɪ boʊ) is a Discord bot that utilizes the discord.py API wrapper to run the bot. Pybo also integrates the
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
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
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.
A Python package for causal inference using Synthetic Controls
Synthetic Control Methods A Python package for causal inference using synthetic controls This Python package implements a class of approaches to estim
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
A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model.
Semantic Meshes A framework for annotating 3D meshes using the predictions of a 2D semantic segmentation model. Paper If you find this framework usefu
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
Real-time ground filtering algorithm of cloud points acquired using Terrestrial Laser Scanner (TLS)
This repository contains tools to simulate the ground filtering process of a registered point cloud. The repository contains two filtering methods. The first method uses a normal vector, and fit to plane. The second method utilizes voxel adjacency, and fit to plane.
Does Oversizing Improve Prosumer Profitability in a Flexibility Market? - A Sensitivity Analysis using PV-battery System
Does Oversizing Improve Prosumer Profitability in a Flexibility Market? - A Sensitivity Analysis using PV-battery System The possibilities to involve
MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets)
MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets) Using mixup data augmentation as reguliraztion and tuning the hyper par
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.
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
OCR Streamlit App is used to extract text from images using python's easyocr, pytorch and streamlit packages
OCR-Streamlit-App OCR Streamlit App is used to extract text from images using python's easyocr, pytorch and streamlit packages OCR app gets an image a
An example project using OpenPrompt under pytorch-lightning for prompt-based SST2 sentiment analysis model
pl_prompt_sst An example project using OpenPrompt under the framework of pytorch-lightning for a training prompt-based text classification model on SS
Crypto Stats and Tweets Data Pipeline using Airflow
Crypto Stats and Tweets Data Pipeline using Airflow Introduction Project Overview This project was brought upon through Udacity's nanodegree program.
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
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