Python Fair-mixup Resources

STEMM: Self-learning with Speech-Text Manifold Mixup for Speech Translation This is a PyTorch implementation for the ACL 2022 main conference paper ST

☑️ FAIR test fair-test is a library to build and deploy FAIR metrics tests APIs supporting the specifications used by the FAIRMetrics working group. I

Primedice like provably fair algorithm

Fair pricing Source code for WWW 2022 paper Regulatory Instruments for Fair Personalized Pricing. Installation Requirements Linux with Python = 3.6 p

☑️ FAIR Enough metrics for research FAIR Enough Metrics is an API for various FAIR Metrics Tests, written in python, conforming to the specifications

Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022) We consider how a user of a web servi

Predict the output which should give a fair idea about the chances of admission for a student for a particular university.

Overview This Python package provides implementations of Augmented Principal Component Analysis (AugmentedPCA) - a family of linear factor models that

schemasheets - structuring your data using spreadsheets Create a data dictionary / schema for your data using simple spreadsheets - no coding required

Fairstructure - Structure your data in a FAIR way using google sheets or TSVs. These are then converted to LinkML, and from there other formats

tendermint-tax A tool to help calculate the tax liability of staking rewards on Tendermint chains. Specifically, this tool calculates the fair market

OpenSelfSup News Downstream tasks now support more methods(Mask RCNN-FPN, RetinaNet, Keypoints RCNN) and more datasets(Cityscapes). 'GaussianBlur' is

fvcore fvcore is a light-weight core library that provides the most common and essential functionality shared in various computer vision frameworks de

TCV-X21 validation for divertor turbulence simulations Quick links Intro Welcome to TCV-X21. We're glad you've found us! This repository is designed t

About The Project This is a code for bitcoin fair value, its simply exclude bubble data using RANSAC method, and then plot the results. Check youtube

PySlowFast PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficie

Manifold Mixup Unofficial implementation of ManifoldMixup (Proceedings of ICML 19) for fast.ai (V2) based on Shivam Saboo's pytorch implementation of

MixRNet(Using mixup as regularization and tuning hyper-parameters for ResNets) Using mixup data augmentation as reguliraztion and tuning the hyper par

SnapMix: Semantically Proportional Mixing for Augmenting Fine-grained Data (AAAI 2021) PyTorch implementation of SnapMix | paper Method Overview Cite

What's New Below we share, in reverse chronological order, the updates and new releases in VISSL. All VISSL releases are available here. [Oct 2021]: V

Fair Recommendation in Two-Sided Platforms

Fair-SSL Source Code for ICSE 2022 Paper - Can We Achieve Fairness Using Semi-Supervised Learning? Ethical bias in machine learning models has become

AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems

DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using

MIST Training MIST TRAIN_FILE=/your/path/to/train.json VALID_FILE=/your/path/to/valid.json OUTPUT_DIR=/your/path/to/save_checkpoints CACHE_DIR=/your/p

MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t

FairGo WWW2021 Learning Fair Representations for Recommendation: A Graph-based Perspective As a key application of artificial intelligence, recommende

FairGNN A PyTorch implementation of "Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information" (

Mixup-Data-Dependency Code associated with the paper "Towards Understanding the Data Dependency of Mixup-style Training". Running Alternating Line Exp

♻️ FAIR enough 🎯 An OpenAPI where anyone can run evaluations to assess how compliant to the FAIR principles is a resource, given the resource identif

Mixup: Beyond Empirical Risk Minimization in PyTorch This is an unofficial PyTorch implementation of mixup: Beyond Empirical Risk Minimization. The co

How to Reproduce our Results This repository contains PyTorch implementation code for the paper MixCo: Mix-up Contrastive Learning for Visual Represen

Pancakeswap-sniper Pancakeswap Sniper bot Full version of Pancakeswap sniping bot used to snipe during fair coin launches. With advanced options and a

MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t

LADA This repo contains codes for the following paper: Jiaao Chen*, Zhenghui Wang*, Ran Tian, Zichao Yang, Diyi Yang: Local Additivity Based Data Augm

Self-Supervised Learning for Domain Adaptation on Point-Clouds Introduction Self-supervised learning (SSL) allows to learn useful representations from

Introduction PyTorch3D provides efficient, reusable components for 3D Computer Vision research with PyTorch. Key features include: Data structure for

TedEval: A Fair Evaluation Metric for Scene Text Detectors Official Python 3 implementation of TedEval | paper | slides Chae Young Lee, Youngmin Baek,

Fair Mixup: Fairness via Interpolation Training classifiers under fairness constraints such as group fairness, regularizes the disparities of predicti

Detectron2 is Facebook AI Research's next generation software system that implements state-of-the-art object detection algorithms. It is a ground-up r

Detectron is deprecated. Please see detectron2, a ground-up rewrite of Detectron in PyTorch. Detectron Detectron is Facebook AI Research's software sy