Topic: "uncertainty-sampling"
ntucllab/libact
Pool-based active learning in Python
Language: Python - Size: 1.86 MB - Last synced at: 1 day ago - Pushed at: 16 days ago - Stars: 785 - Forks: 173
SURGroup/UQpy
UQpy (Uncertainty Quantification with python) is a general purpose Python toolbox for modeling uncertainty in physical and mathematical systems.
Language: Python - Size: 173 MB - Last synced at: 25 days ago - Pushed at: about 1 month ago - Stars: 311 - Forks: 82
baggepinnen/MonteCarloMeasurements.jl
Propagation of distributions by Monte-Carlo sampling: Real number types with uncertainty represented by samples.
Language: Julia - Size: 4.91 MB - Last synced at: 2 days ago - Pushed at: 2 days ago - Stars: 274 - Forks: 17
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:
Language: Python - Size: 6.54 MB - Last synced at: about 1 month ago - Pushed at: over 5 years ago - Stars: 202 - Forks: 55
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.
Language: Java - Size: 10.7 MB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 10 - Forks: 4
ahhaque/SAND
SAND: Semi-Supervised Adaptive Novel Class Detection and Classification over Data Stream
Language: Java - Size: 10.7 MB - Last synced at: over 1 year ago - Pushed at: over 7 years ago - Stars: 10 - Forks: 5
tupui/PHD-Thesis
PHD Thesis at CERFACS: Uncertainty Quantification for High Dimensional Problems
Language: TeX - Size: 135 MB - Last synced at: 2 months ago - Pushed at: over 4 years ago - Stars: 3 - Forks: 1
ryanquinnnelson/CMU-02750-Query-Selection-Methods-in-Active-Learning
Spring 2021 - Automation of Scientific Research - course project
Language: Jupyter Notebook - Size: 4.59 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 1
sid-devic/OpAL
Open Active Learning for Deep Models
Language: Python - Size: 44.9 KB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 0
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.
Language: Python - Size: 3.08 MB - Last synced at: 3 months ago - Pushed at: 9 months ago - Stars: 0 - Forks: 1
