Pool-based AL Strategies#
Density-Diversity-Distribution-Distance Sampling (4DS)
Density-Diversity-Distribution-Distance Sampling (4DS)
Querying Informative and Representative Examples (QUIRE)
Querying Informative and Representative Examples (QUIRE)
Uncertainty Sampling with Expected Average Precision (USAP)
Uncertainty Sampling with Expected Average Precision (USAP)
Monte-Carlo Expected Error Reduction (EER) with Log-Loss
Monte-Carlo Expected Error Reduction (EER) with Log-Loss
Monte-Carlo Expected Error Reduction (EER) with Misclassification-Loss
Monte-Carlo Expected Error Reduction (EER) with Misclassification-Loss
Query-by-Committee (QBC) with Kullback-Leibler Divergence
Query-by-Committee (QBC) with Kullback-Leibler Divergence
Batch Active Learning by Diverse Gradient Embedding (BADGE)
Batch Active Learning by Diverse Gradient Embedding (BADGE)
Batch Density-Diversity-Distribution-Distance Sampling (4DS)
Batch Density-Diversity-Distribution-Distance Sampling (4DS)
Fast Active Learning by Contrastive UNcertainty (FALCUN)
Fast Active Learning by Contrastive UNcertainty (FALCUN)
Batch Bayesian Active Learning by Disagreement (BatchBALD)
Batch Bayesian Active Learning by Disagreement (BatchBALD)