uncertainty-sampling
There are 10 repositories under uncertainty-sampling topic.
ntucllab/libact
Pool-based active learning in Python
SURGroup/UQpy
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
baggepinnen/MonteCarloMeasurements.jl
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
dsgissin/DiscriminativeActiveLearning
Code and website for DAL (Discriminative Active Learning) - a new active learning algorithm for neural networks in the batch setting. For the blog:
ahhaque/SAND
SAND: Semi-Supervised Adaptive Novel Class Detection and Classification over Data Stream
ahhaque/ECHO
ECHO is a semi-supervised framework for classifying evolving data streams based on our previous approach SAND. The most expensive module of SAND is the change detection module, which has cubic time complexity. ECHO uses dynamic programming to reduce the time complexity. Moreover, ECHO has a maximum allowable sliding window size. If there is no concept drift detected within this limit, ECHO updates the classifiers and resets the sliding window. Experiment results show that ECHO achieves significant speed up over SAND while maintaining similar accuracy. Please refer to the paper (mentioned in the reference section) for further details.
ryanquinnnelson/CMU-02750-Query-Selection-Methods-in-Active-Learning
Spring 2021 - Automation of Scientific Research - course project
tupui/PHD-Thesis
PHD Thesis at CERFACS: Uncertainty Quantification for High Dimensional Problems
sid-devic/OpAL
Open Active Learning for Deep Models
eurobios-mews-labs/active-bagging-learning
This library proposes a plug-in approach to active learning utilizing bagging techniques. Bagging, or bootstrap aggregating, is an ensemble learning method designed to improve the stability and accuracy of machine learning algorithms.