Bayesian Active Learning for Remote Sensing
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Updated
Jul 22, 2020 - MATLAB
Bayesian Active Learning for Remote Sensing
Active learning-guided exploration of parameter space of air plasmas to enhance the energy efficiency of NO x production
Project source code and data for risk estimation with an imperfect Machine learning model
This is a repository associated with the paper "Near-optimal sampling strategies for multivariate function on general domains" by Ben Adcock and Juan M. Cardenas available at https://epubs.siam.org/doi/10.1137/19M1279459 and https://arxiv.org/abs/1908.01249
Active versus Passive exploration
This is a repository for CS4ML. It is a general framework for active learning in regression problems. It approximates a target function arising from general types of data, rather than pointwise samples.
Active Learning combining Online Semi-Supervised Dictionary Learning
Quantile set inversion [arXiv:2211.01008] — Numerical experiments
Gaussian Processes for Cyclic Voltammetry
This repository contains the code to reproduce all of the results in our paper: Nuclear discrepancy for single-shot batch active learning, Tom J Viering, Jesse H Krijthe, Marco Loog, in Machine Learning 2019.
The code of ''Single Shot Active Learning using Pseudo Annotators"
A toolbox for Weighted Sparse Simplex Representation (WSSR).
Language Agnostic Syllabification with Active Learning
Domain Adaptation by Transferring Model-Complexity Priors Across Tasks Paper Experiments
Matlab source code of the paper: D. Wu, "Pool-based sequential active learning for regression," IEEE Trans. on Neural Networks and Learning Systems, 30(5), pp. 1348-1359, 2019.
Matlab code of the IRD algorithm in the paper: 刘子昂, 蒋雪, 伍冬睿, "基于池的无监督线性回归主动学习," 自动化学报, 2020. Or the English version here: https://arxiv.org/pdf/2001.05028.pdf
ALPUD: Active Learning from Positive and Unlabeled Data
Active Learning Project
The demo partially associated with the following papers: "Spatial Prior Fuzziness Pool-Based Interactive Classification of Hyperspectral Images" and "Multiclass Non-Randomized Spectral–Spatial Active Learning for Hyperspectral Image Classification".
The Matlab code of "A Variance Maximization Criterion for Active Learning"
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