Pool-based AL Strategies#
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)
Density-Diversity-Distribution-Distance Sampling (4DS)
Density-Diversity-Distribution-Distance Sampling (4DS)
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)
Fast Active Learning by Contrastive UNcertainty (FALCUN)
Fast Active Learning by Contrastive UNcertainty (FALCUN)
Batch Density-Diversity-Distribution-Distance Sampling (4DS)
Batch Density-Diversity-Distribution-Distance Sampling (4DS)
Batch Bayesian Active Learning by Disagreement (BatchBALD)
Batch Bayesian Active Learning by Disagreement (BatchBALD)