| Year | Title | Author | Publication | Code | Tasks | Notes | Datasets | Notions |
|---|---|---|---|---|---|---|---|---|
| 2022 | Deep Multi-Fidelity Active Learning of High-Dimensional Outputs | Li et al. | AISTATS | code | DMFAL to predict the solution fields of three commonly used partial differential equations (PDEs): Burgers ’ , Poisson ’s and Heat equations | Mutual Information, DNNs |
||
| 2022 | Safe Active Learning for Multi-Output Gaussian Processes | Li et al. | AISTATS | code | Multi-output regression problems | Informative, Gaussian processes, None, Tra, Hard |
simulation with sin & sigmoid, MOGP samples, Engine Emission (EngE) Dataset | |
| 2022 | Multi-class classification in nonparametric active learning | Njike et al. | AISTATS | - | multiclass classification | k-nearest neighbors, BNNs, None, Tra, Hard |
Synthetic Datasets | |
| 2022 | Nuances in Margin Conditions Determine Gains in Active Learning | Kpotufe et al. | AISTATS | - | nonparametric classification | margin condition, Bayes classifier, None, Tra, Hard |
- |