NUAA-AL / ALiPy
ALiPy: Active Learning in Python is an active learning python toolbox, which allows users to conveniently evaluate, compare and analyze the performance of active learning methods.
☆867Updated 2 years ago
Related projects: ⓘ
- ☆1,113Updated last year
- Deep Active Learning☆795Updated last year
- PyTorch Library for Active Learning to accompany Human-in-the-Loop Machine Learning book☆930Updated last year
- A modular active learning framework for Python☆2,193Updated 6 months ago
- Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting. For…☆200Updated 4 years ago
- Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.☆230Updated 3 months ago
- A curated list of awesome Active Learning☆709Updated 3 months ago
- ☆1,135Updated last year
- [NeurIPS 2020] Semi-Supervision (Unlabeled Data) & Self-Supervision Improve Class-Imbalanced / Long-Tailed Learning☆736Updated 3 years ago
- Source code for ICLR 2018 Paper: Active Learning for Convolutional Neural Networks: A Core-Set Approach☆259Updated 5 years ago
- Pool-based active learning in Python☆776Updated last year
- Bayesian active learning library for research and industrial usecases.☆859Updated 2 months ago
- Awesome Multitask Learning Resources☆636Updated 3 years ago
- Everything you need about Active Learning (AL).☆780Updated 3 months ago
- Unsupervised Data Augmentation (UDA)☆2,172Updated 3 years ago
- A simple method to perform semi-supervised learning with limited data.☆1,089Updated last month
- A multi-task learning example for the paper https://arxiv.org/abs/1705.07115☆839Updated 4 years ago
- 😎 Everything about class-imbalanced/long-tail learning: papers, codes, frameworks, and libraries | 有关类别不平衡/长尾学习的一切:论文、代码、框架与库☆1,345Updated 4 months ago
- Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet☆604Updated last year
- An implementation of the BADGE batch active learning algorithm.☆193Updated 3 months ago
- [NeurIPS 2019] Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss☆634Updated 2 years ago
- Metric learning algorithms in Python☆1,395Updated last month
- Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"☆781Updated 7 months ago
- NeurIPS'18: Co-teaching: Robust Training of Deep Neural Networks with Extremely Noisy Labels☆486Updated 3 years ago
- [ICML 2021, Long Talk] Delving into Deep Imbalanced Regression☆806Updated 2 years ago
- This repo consists of collection of papers and repos on the topic of deep learning by noisy labels / label noise.☆236Updated 3 years ago
- A curated list of resources for Learning with Noisy Labels☆2,621Updated 4 months ago
- This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 202…☆938Updated 2 years ago
- Variational Adversarial Active Learning (ICCV 2019)☆223Updated last year
- Learning to Cluster. A deep clustering strategy.☆313Updated 4 years ago