Efficiently Learning Relative Similarity Embeddings with Crowdsourcing
Efficiently Learning Relative Similarity Embeddings with Crowdsourcing - Published in JOSS (2023)
scikit-activeml
scikit-activeml: Python library for active learning on top of scikit-learn
dpgen
The deep potential generator to generate a deep-learning based model of interatomic potential energy and force field
active-learning-as-a-service
A scalable & efficient active learning/data selection system for everyone.
monailabel
MONAI Label is an intelligent open source image labeling and learning tool.
asreview-insights
Tools such as plots and metrics to analyze (simulated) reviews for ASReview LAB
deep_active_learning_biore
Framework to study the use of deep active learning for biomedical relation extraction
calisim-examples-workshop-material
Workshop for calisim: A toolbox for the calibration and evaluation of simulation models.
calisim
A toolbox for the calibration and evaluation of simulation models.
marich
Marich is a model-agnostic extraction algorithm. It uses a public data to query a private model, aggregates the predicted labels, and construct a distributionall equivalent/max-information leaking extracted model.
pyepal
Multiobjective active learning with tunable accuracy/efficiency tradeoff and clear stopping criterion.
bachelor_thesis_project
System for Training-based Expansion of Tools for Proper Name Mentions Recognition Based on Active Learning