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102 search results found

Modal ⭐ 2,057

A modular active learning framework for Python

Refinery ⭐ 1,257

The data scientist's open-source choice to scale, assess and maintain natural language data. Treat training data like a software artifact.

Adaptive ⭐ 1,079

📈 Adaptive: parallel active learning of mathematical functions

Library to enable Bayesian active learning in your research or labeling work.

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.

Ad_examples ⭐ 738

A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.

Pool-based active learning in Python

Deep Active Learning ⭐ 553

Deep Active Learning

Asreview ⭐ 525

Active learning for systematic reviews

Small Text ⭐ 509

Active Learning for Text Classification in Python

Monailabel ⭐ 496

MONAI Label is an intelligent open source image labeling and learning tool.

Encord Active ⭐ 385

The toolkit to test, validate, and evaluate your models and surface, curate, and prioritize the most valuable data for labeling.

Code for Multiple Instance Active Learning for Object Detection, CVPR 2021

The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field

Label Sleuth ⭐ 230

Open source no-code system for text annotation and building of text classifiers

Smarter Manual Annotation for Resource-constrained collection of Training data

Active Learning As A Service ⭐ 206

A scalable & efficient active learning/data selection system for everyone.

Seal Ci ⭐ 201

A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)

Aerial_wildlife_detection ⭐ 177

Tools for detecting wildlife in aerial images using active learning

Batchbald ⭐ 174

Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning.

Gaussian Processes for Experimental Sciences

Bamboo: 4 times larger than ImageNet; 2 time larger than Object365; Built by active learning.

[CVPR'20] Implementation for the paper "ViewAL: Active Learning with Viewpoint Entropy for Semantic Segmentation"

A Bayesian Back End for Design of Experiments

Scikit Activeml ⭐ 101

Our package scikit-activeml is a Python library for active learning on top of SciPy and scikit-learn.

Face_recognition_crop ⭐ 96

Recognize, Crop and Save Multi-View Faces as Images From Video to Create a Multi-View Face Database.

Discriminativeactivelearning ⭐ 81

Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting. For the blog:

Doccano Client ⭐ 76

A simple client for doccano API.

Trunklucator ⭐ 73

Python module for data scientists for quick creating annotation projects.

Icl Selective Annotation ⭐ 72

[ICLR 2023] Code for our paper "Selective Annotation Makes Language Models Better Few-Shot Learners"

Deep Active Learning ⭐ 72

An implementation of the state-of-the-art Deep Active Learning algorithms

Energizer ⭐ 71

An active learning library for Pytorch based on Pytorch-Lightning.

[AAAI 2022] Official Implementation of Active Learning for Domain Adaptation: An Energy-based Approach https://arxiv.org/abs/2112.01406

Medcattrainer ⭐ 62

A simple interface to inspect, improve and add concepts to biomedical NER+L -> MedCAT.

Alpha_mix_active_learning ⭐ 52

The official implementation of Active Learning by Feature Mixing (ALFA-Mix) paper

Contrastive Active Learning ⭐ 51

Code for the EMNLP 2021 Paper "Active Learning by Acquiring Contrastive Examples" & the ACL 2022 Paper "On the Importance of Effectively Adapting Pretrained Language Models for Active Learning"

Human In The Loop Machine Learning Tool Tornado ⭐ 49

Tornado is a human-in-the-loop machine learning framework that helps you exploit your unlabelled data to train models through a simple and easy to use web interface.

Astronomical ⭐ 47

An interactive dashboard for visualisation, integration and classification of data using Active Learning.

Cardinal ⭐ 47

A practical Active Learning python package with a strong focus on experiments.

Official PyTorch implementation of "PT4AL: Using Self-Supervised Pretext Tasks for Active Learning (ECCV2022)"

tools for fast reading of docs

Crb Active 3ddet ⭐ 33

The official PyTorch implementation of "Exploring Active 3D Object Detection from a Generalization Perspective" (ICLR Spotlight 2023).

PyTorch Implementation of Temporal Output Discrepancy for Active Learning, ICCV 2021

A Python library for Robotic Information Gathering

Cardinal ⭐ 28

A practical Active Learning python package with a strong focus on experiments.

Multiobjective active learning with tunable accuracy/efficiency tradeoff and clear stopping criterion.

Al Fk Self Supervision ⭐ 25

Official PyTorch code for CVPR 2020 paper "Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision"

Adaptive Scheduler ⭐ 24

Run many functions (adaptively) on many cores (>10k) using mpi4py.futures, ipyparallel, loky, or dask-mpi. 🎉

Plug and Play Active Learning for Object Detection

Asreview Insights ⭐ 23

Tools such as plots and metrics to analyze (simulated) reviews for ASReview LAB

Differential Privacy Bayesian Optimization ⭐ 22

This repo contains the underlying code for all the experiments from the paper: "Automatic Discovery of Privacy-Utility Pareto Fronts"

Active Bayesian Causal Inference ⭐ 21

Active Bayesian Causal Inference (Neurips'22)

Towards Human-Machine Cooperation: Self-supervised Sample Mining for Object Detection

ReBound is an open-source, LiDAR visualization and annotation tool to assist active-learning systems involved in autonomous vehicles

Vatl4pose Wacv2024 ⭐ 19

[WACV2024] Official PyTorch implimentation for ``Active Transfer Learning for Efficient Video-Specific Human Pose Estimation''

Active Explainable Classification ⭐ 19

A set of tools for leveraging pre-trained embeddings, active learning and model explainability for effecient document classification

Deep Reinforcement One-Shot Learning Framework for Artificially Intelligent Classification Systems

Ceal_keras ⭐ 18

Implementation of "Cost-Effective Active Learning for Deep Image Classification" paper

Deep Active Learning For Joint Classification And Segmentation With Weak Annotator ⭐ 18

Pytorch code for the paper "Deep Active Learning for Joint Classification and Segmentation with Weak Annotator"

labelit, label tool with active learning, for classification task. 自动标注，基于主动学习，边标注边学习，减少人工标注量。

Refinery Python Sdk ⭐ 17

Official Python SDK for Kern AI refinery.

Nbtransom ⭐ 17

Machines and people collaborating together through Jupyter notebooks.

[ICLR 2020] Learning to Move with Affordance Maps 🤖💨🗺️

Yolov7_labelstudio ⭐ 17

Fine tuning YoloV7 to detect white, red bloodcells and platelets to be used as backend in label studio for pre annotating

Chemprop ⭐ 16

Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.

Probabilistic Response mOdel Fitting with Interactive Tools

🍀 Official pytorch implementation of "D2ADA: Dynamic Density-aware Active Domain Adaptation for Semantic Segmentation. Wu et al. ECCV 2022."

Amons-based quantum machine learning for quantum chemistry

Optical Flow Active Learning Release ⭐ 13

The official PyTorch implementation of the paper "Optical Flow Training under Limited Label Budget via Active Learning" (ECCV 2022)

[ACL 2023] The code for our ACL'23 paper Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation Approach

Submodular Subset Selection for Active Domain Adaptation (ICCV 2021)

HiCAL is a system for efficient high-recall retrieval with an adaptable assessing interface.

O-MedAL: Online Active Deep Learning for Medical Image Analysis. This repo contains code for the paper.

Entitytargetedactivelearning ⭐ 12

Code for A-LINK and A2-LINK

[ICCV-23] Official implementation of SeedAL for seeding active learning for 3D semantic segmentation

Code accompanying EMNLP 2020 paper "Cold-start Active Learning through Self-supervised Language Modeling".

Move2hear Active Av Separation ⭐ 11

Code and datasets for 'Move2Hear: Active Audio-Visual Source Separation' (ICCV 2021)

Waffle_utils ⭐ 10

🧇Waffle Utils🧇 is a set of utilities for waffle components

Local Context-Aware Active Domain Adaptation (ICCV 2023)

An opensource TAR framework for experiments and applications

Focusing on potential named entities during active label acquisition.

Changedetectionproject ⭐ 8

Change Detection project - the more experimental build version. Trying out Active Learning in with deep CNNs for Change detection on remote sensing data.

Physics_world_rl ⭐ 8

Implementation of CogSci 2019 paper 'Active physical learning via reinforcement learning'

ALBench Leaderboard for active learning in object detection

A no-programming Machine Learning platform for Material Design

Spotify Music Discovery ⭐ 8

🎧 create your own spotify recommendation algorithm

Qdrant Nlp ⭐ 7

Star Framework ⭐ 7

Code for L2ID CVPRW 2021 paper Improving Semi-Supervised Domain Adaptation Using Effective Target Selection and Semantics

Pac_learn_rtas ⭐ 7

🔧 A prototype tool on learning real-time automata based on pac.

Information-Theoretic Active Learning

Implementation of the paper "Deep Indexed Active Learning for Matching Heterogeneous Entity Representations"

Python implementation of lstar automata learning algorithm.

A tool to collect triplet queries

Actively Reducing Redundancies In Active Learning For Sequence Tagging ⭐ 6

Active Learning for sequence tagging

PyTorch implementation of VirAAL: Virtual Adversarial Active Learning (https://arxiv.org/abs/2005.07287)

BAL: Balancing Diversity and Novelty for Active Learning - Official Pytorch Implementation

User-friendly Graphical User Interface (GUI) developed at the National Institute for Materials Science (NIMS) for performing statistical data analysis, machine learning (ML) modelisation, and composition/process optimisation through active learning assisted by Bayesian optimisation

Ecg_activelearning ⭐ 5

Dataset and code for "Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning"

Ea Active Learning ⭐ 5

Code for paper "Active Learning for Entity Alignment" (https://arxiv.org/abs/2001.08943)

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