Python Data-efficient-learning Resources

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

PyTorch code for the paper "Curriculum Graph Co-Teaching for Multi-target Domain Adaptation" (CVPR2021) This repo presents PyTorch implementation of M

Neural Reprojection Error: Merging Feature Learning and Camera Pose Estimation This is the official repository for our paper Neural Reprojection Error

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

A Python Library for Document Layout Understanding

Apache Superset is a Data Visualization and Data Exploration Platform

Oppia is an online learning tool that enables anyone to easily create and share interactive activities (called 'explorations'). These activities simulate a one-on-one conversation with a tutor, making it possible for students to learn by doing while getting feedback.

FAU Implementation of the paper: Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution. Yingruo

MVFNet: Multi-View Fusion Network for Efficient Video Recognition (AAAI 2021) Overview We release the code of the MVFNet (Multi-View Fusion Network).

New Benchmarks for Learning on Non-Homophilous Graphs Here are the codes and datasets accompanying the paper: New Benchmarks for Learning on Non-Homop

Introduction Pytorch implementation of Multiple Heads are Better than One: Few-shot Font Generation with Multiple Localized Expert. | paper Song Park1

Distribution Analyser Distribution Analyser is a Web App that allows you to interactively explore continuous distributions from SciPy and fit distribu

emb-ntua-workshop This workshop discusses introductory concepts of machine learning and data mining following a hands-on approach using popular tools

Polyglot Machine Learning example for scraping similar news articles In this example, we will see how we can work with Machine Learning applications w

TransGanFormer (wip) Implementation of TransGanFormer, an all-attention GAN that combines the finding from the recent GansFormer and TransGan paper. I

Dynamic Slimmable Network (DS-Net) This repository contains PyTorch code of our paper: Dynamic Slimmable Network (CVPR 2021 Oral). Architecture of DS-

MARL Tricks Our codes for RIIT: Rethinking the Importance of Implementation Tricks in Multi-AgentReinforcement Learning. We implemented and standardiz

提要 持续收集原神抽卡记录中 可以使用抽卡记录导出工具导出抽卡记录的json，将json文件发送至[email protected]，我会在清除个人信息后将文件提交到此处。以下两种导出工具任选其一即可。 一种抽卡记录导出工具 from sunfkny 使用方法演示视频 另一种electron版的抽

Cutoff: A Simple Data Augmentation Approach for Natural Language This repository contains source code necessary to reproduce the results presented in

CheXbert: Combining Automatic Labelers and Expert Annotations for Accurate Radiology Report Labeling Using BERT CheXbert is an accurate, automated dee

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

InversePrompting Paper: Controllable Generation from Pre-trained Language Models via Inverse Prompting Code: The code is provided in the "chinese_ip"

UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language This repository contains UA-GEC data and an accompanying Python lib

Machine Learning Conference & Summer School Notes. 🦄📝🎉

Neural-Semi-supervised-Learning-for-Text-Classification-Under-Large-Scale-Pretraining Code, models and Datasets for《Neural Semi-supervised Learning fo

An open-source library of algorithms to analyse time series in GPU and CPU.

Pixel-level Self-Paced Learning for Super-Resolution This is an official implementaion of the paper Pixel-level Self-Paced Learning for Super-Resoluti

DNA This repository provides the code of our paper: Blockwisely Supervised Neural Architecture Search with Knowledge Distillation. Illustration of DNA

Regularizing Generative Adversarial Networks under Limited Data [Project Page][Paper] Implementation for our GAN regularization method. The proposed r

Improving Unsupervised Image Clustering With Robust Learning This repo is the PyTorch codes for "Improving Unsupervised Image Clustering With Robust L

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

The Picasso Library is intended for complex real-world applications with large-scale surfaces, while it also performs impressively on the small-scale applications over synthetic shape manifolds. We have upgraded the point cloud modules of SPH3D-GCN from homogeneous to heterogeneous representations, and included the upgraded modules into this latest work as well. We are happy to announce that the work is accepted to IEEE CVPR2021.

Personalized Federated Learning with Moreau Envelopes (NeurIPS 2020) This repository implements all experiments in the paper Personalized Federated Le

The Most Important Thing. Our code is developed based on: LXMERT: Learning Cross-Modality Encoder Representations from Transformers

DAL This project hosts the official implementation for our AAAI 2021 paper: Dynamic Anchor Learning for Arbitrary-Oriented Object Detection [arxiv] [c

UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning This is the official PyTorch implementation for UniMoCo pape

This project is part of Eleuther AI's quest to create a massive repository of high quality text data for training language models.

Bloodhound for Linux Ingest a dumped OpenLDAP ldif into neo4j to be visualized in Bloodhound. Usage: ./ldif_to_neo4j.py ./sample.ldif | cypher-shell -

Practical Machine Learning Workshop Series Practical Machine Learning for Quantitative Finance Post conference workshop at the WBS Spring Conference D

Description Using hotel data and AI to predict high value guests and potential VIP guests. Hotel can leverage on prediction resutls to run more effect

Flenser Have you ever been handed a dataset you've never seen before? Flenser is a simple, minimal, automated exploratory data analysis tool. It runs

Table of contents What is DOP Design Concept A Typical DOP Orchestration Flow Prerequisites - Run in Docker For DOP Native Features For DBT Instructio

DevResources One destination for all the developer's learning resources. Find all of your learning resources under one roof and add your own. Live ✨ Y

Revamping Cross-Modal Recipe Retrieval with Hierarchical Transformers and Self-supervised Learning This is the PyTorch companion code for the paper: A

Welcome to Cython! Cython is a language that makes writing C extensions for Python as easy as Python itself. Cython is based on Pyrex, but supports mo

IPython: Productive Interactive Computing Overview Welcome to IPython. Our full documentation is available on ipython.readthedocs.io and contains info

DensePhrases DensePhrases provides answers to your natural language questions from the entire Wikipedia in real-time. While it efficiently searches th

STARK The official implementation of the paper Learning Spatio-Temporal Transformer for Visual Tracking Hiring research interns for visual transformer

FewShotText This repository contains code for the paper A Neural Few-Shot Text Classification Reality Check Environment setup # Create environment pyt

Code Transformer This is an official PyTorch implementation of the CodeTransformer model proposed in: D. Zügner, T. Kirschstein, M. Catasta, J. Leskov

The guide to tackle with the Text Summarization

spatial-action-maps Update: Please see our new spatial-intention-maps repository, which extends this work to multi-agent settings. It contains many ne

USD-Seg This project is an implement of paper USD-Seg:Learning Universal Shape Dictionary for Realtime Instance Segmentation, based on FCOS detector f

Pseudo-ISP: Learning Pseudo In-camera Signal Processing Pipeline from A Color Image Denoiser Abstract The success of deep denoisers on real-world colo

DialogBERT This is a PyTorch implementation of the DialogBERT model described in DialogBERT: Neural Response Generation via Hierarchical BERT with Dis

Contact Potential Field This repo contains model, demo, and test codes of our paper: CPF: Learning a Contact Potential Field to Model the Hand-object

Adversarial Training Against Location-Optimized Adversarial Patches arXiv | Paper | Code | Video | Slides Code for the paper: Sukrut Rao, David Stutz,

CPT: Efficient Deep Neural Network Training via Cyclic Precision Yonggan Fu, Han Guo, Meng Li, Xin Yang, Yining Ding, Vikas Chandra, Yingyan Lin Accep

512x512 flowers after 12 hours of training, 1 gpu 256x256 flowers after 12 hours of training, 1 gpu Pizza 'Lightweight' GAN Implementation of 'lightwe

Boltons boltons should be builtins. Boltons is a set of over 230 BSD-licensed, pure-Python utilities in the same spirit as — and yet conspicuously mis

Swin Transformer - PyTorch Implementation of the Swin Transformer architecture. This paper presents a new vision Transformer, called Swin Transformer,

STAM - Pytorch Implementation of STAM (Space Time Attention Model), yet another pure and simple SOTA attention model that bests all previous models in

Viewflow Viewflow is a framework built on the top of Airflow that enables data scientists to create materialized views. It allows data scientists to f

GLOM TensorFlow This Python package attempts to implement GLOM in TensorFlow, which allows advances made by several different groups transformers, neu

STARK The official implementation of the paper Learning Spatio-Temporal Transformer for Visual Tracking Highlights The strongest performances Tracker

deep-significance: Easy and Better Significance Testing for Deep Neural Networks Contents ⁉️ Why 📥 Installation 🔖 Examples Intermezzo: Almost Stocha

Support Me 🚀 About Polaris 📄 Polaris is a system based on facial recognition with a futuristic GUI design, Can easily find people informations store

Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation (CVPR 2021, official Pytorch implementatio

Learning Calibrated-Guidance for Object Detection in Aerial Images arxiv We propose a simple yet effective Calibrated-Guidance (CG) scheme to enhance

DASR Pytorch implementation of "Unsupervised Degradation Representation Learning for Blind Super-Resolution", CVPR 2021 [arXiv] Overview Requirements

The mljar-supervised is an Automated Machine Learning Python package that works with tabular data. I

Repository to track the progress in Natural Language Processing (NLP), including the datasets and the current state-of-the-art for the most common NLP tasks.

ZhuSuan is a Python probabilistic programming library for Bayesian deep learning, which conjoins the complimentary advantages of Bayesian methods and

Edward is a Python library for probabilistic modeling, inference, and criticism. It is a testbed for fast experimentation and research with probabilis

Bayesian Active Learning (BaaL) BaaL is an active learning library developed at ElementAI. This repository contains techniques and reusable components

Funsor Funsor is a tensor-like library for functions and distributions. See Functional tensors for probabilistic programming for a system description.

pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit

Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow

Please consider citing the JMLR-MLOSS Manuscript if you've used pomegranate in your academic work! pomegranate is a package for building probabilistic

GPyTorch GPyTorch is a Gaussian process library implemented using PyTorch. GPyTorch is designed for creating scalable, flexible, and modular Gaussian

Getting Started | Documentation | Community | Contributing Pyro is a flexible, scalable deep probabilistic programming library built on PyTorch. Notab

TensorFlow Probability TensorFlow Probability is a library for probabilistic reasoning and statistical analysis in TensorFlow. As part of the TensorFl

dabl The data analysis baseline library. "Mr Sanchez, are you a data scientist?" "I dabl, Mr president." Find more information on the website. State o

skope-rules Skope-rules is a Python machine learning module built on top of scikit-learn and distributed under the 3-Clause BSD license. Skope-rules a

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

Scikit-TDA is a home for Topological Data Analysis Python libraries intended for non-topologists. This project aims to provide a curated library of TD

iterative-stratification iterative-stratification is a project that provides scikit-learn compatible cross validators with stratification for multilab

DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and

scikit-lego We love scikit learn but very often we find ourselves writing custom transformers, metrics and models. The goal of this project is to atte

combo: A Python Toolbox for Machine Learning Model Combination Deployment & Documentation & Stats Build Status & Coverage & Maintainability & License

lightning lightning is a library for large-scale linear classification, regression and ranking in Python. Highlights: follows the scikit-learn API con

Mlxtend (machine learning extensions) is a Python library of useful tools for the day-to-day data science tasks. Sebastian Raschka 2014-2021 Links Doc

imbalanced-learn imbalanced-learn is a python package offering a number of re-sampling techniques commonly used in datasets showing strong between-cla

Here is Poutyne. Poutyne is a simplified framework for PyTorch and handles much of the boilerplating code needed to train neural networks. Use Poutyne

Tez: a simple pytorch trainer NOTE: Currently, we are not accepting any pull requests! All PRs will be closed. If you want a feature or something does

Pywick High-Level Training framework for Pytorch Pywick is a high-level Pytorch training framework that aims to get you up and running quickly with st

PyTorch Implementation of Differentiable SDE Solvers This library provides stochastic differential equation (SDE) solvers with GPU support and efficie

Lambda Networks - Pytorch Implementation of λ Networks, a new approach to image recognition that reaches SOTA on ImageNet. The new method utilizes λ l

Performer - Pytorch An implementation of Performer, a linear attention-based transformer variant with a Fast Attention Via positive Orthogonal Random