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

Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learn

Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee

MONAI Label is a server-client system that facilitates interactive medical image annotation by using AI. It is an open-source and easy-to-install ecosystem that can run locally on a machine with one

A Simple Baseline for Low-Budget Active Learning This repository is the implementation of A Simple Baseline for Low-Budget Active Learning. In this pa

This is the Vowpal Wabbit fast online learning code. Why Vowpal Wabbit? Vowpal Wabbit is a machine learning system which pushes the frontier of machin

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

Awesome Active Learning 🤩 A curated list of awesome Active Learning ! 🤩 Background (image source: Settles, Burr) What is Active Learning? Active lea

SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

DISTIL: Deep dIverSified inTeractIve Learning. An active/inter-active learning library built on py-torch for reducing labeling costs.

Data Annotation, Data Labeling, Annotation Tooling, Training Data for Machine Learning

DeepAL: Deep Active Learning in Python Python implementations of the following active learning algorithms: Random Sampling Least Confidence [1] Margin

AstronomicAL An interactive dashboard for visualisation, integration and classification of data using Active Learning. AstronomicAL is a human-in-the-

Deep Active Learning for Biased Datasets via Fisher Kernel Self-Supervision https://arxiv.org/abs/2003.00393 Abstract Active learning (AL) aims to min

This repository contains the software implementation of most algorithms used or developed in my research. The LaTeX and Python code for generating the

Modular Active Learning framework for Python3 Page contents Introduction Active learning from bird's-eye view modAL in action From zero to one in a fe

Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee

adaptive Adaptive: parallel active learning of mathematical functions. adaptive is an open-source Python library designed to make adaptive parallel fu

✨A Python framework to explore, label, and monitor data for NLP projects

Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate

Temporal Output Discrepancy for Active Learning PyTorch implementation of Semi-Supervised Active Learning with Temporal Output Discrepancy, ICCV 2021.

S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation ICCV 2021 Harsh Rangwani, Arihant Jain*, Sumukh K Aithal*, R. Ve

Active Learning allows you to efficiently label training data in a small-data scenario.

MI-AOD Language: 简体中文 | English Introduction This is the code for Multiple Instance Active Learning for Object Detection (The PDF is not available tem

Language: 简体中文 | English Introduction This is the code for Multiple Instance Active Learning for Object Detection, CVPR 2021. Installation A Linux pla