Name
Title | ||
|---|---|---|
A survey on epistemic (model) uncertainty in supervised learning: Recent advances and applications |
Abstract | ||
|---|---|---|
•A review of epistemic (model) uncertainty learning in supervised learning is provided.•The predictive uncertainty is discussed from the prospective generalization error.•A hierarchical categorization of epistemic uncertainty learning techniques are introduced.•Applications of epistemic uncertainty learning in CV and NLP are presented.•Main research gaps along with future research directions are pointed out. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1016/j.neucom.2021.10.119 | Neurocomputing |
Keywords | DocType | Volume |
Epistemic uncertainty learning,Supervised learning,Bayesian approximation,Ensemble learning,Computer vision,Natural language processing | Journal | 489 |
ISSN | Citations | PageRank |
0925-2312 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xinlei Zhou | 1 | 0 | 1.35 |
| Han Liu | 2 | 1 | 2.71 |
| Farhad Pourpanah | 3 | 0 | 0.34 |
| Tieyong Zengd | 4 | 0 | 0.34 |
| Xizhao Wang | 5 | 3593 | 166.16 |