2 citations · 2 across the 3 of their papers we have counts for
3 papers
stat.ML2024
DSDE: Using Proportion Estimation to Improve Model Selection for Out-of-Distribution Detection
Jingyao Geng, Yuan Zhang, Jiaqi Huang +4
Model library is an effective tool for improving the performance of single-model Out-of-Distribution (OoD) detector, mainly through model selection and detector fusion. However, ex…
cs.LG2024
Enhancing Out-of-Distribution Detection with Multitesting-based Layer-wise Feature Fusion
Jiawei Li, Sitong Li, Shanshan Wang +3
Deploying machine learning in open environments presents the challenge of encountering diverse test inputs that differ significantly from the training data. These out-of-distributi…
cs.LG2023★ 2 cited
Boosting Out-of-Distribution Detection with Multiple Pre-trained Models
Feng Xue, Zi He, Chuanlong Xie +2
Out-of-Distribution (OOD) detection, i.e., identifying whether an input is sampled from a novel distribution other than the training distribution, is a critical task for safely dep…