2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CV2023
SupEuclid: Extremely Simple, High Quality OoD Detection with Supervised Contrastive Learning and Euclidean Distance
Jarrod Haas
Out-of-Distribution (OoD) detection has developed substantially in the past few years, with available methods approaching, and in a few cases achieving, perfect data separation on…
cs.LG2023
Exploring Simple, High Quality Out-of-Distribution Detection with L2 Normalization
Jarrod Haas, William Yolland, Bernhard Rabus
We demonstrate that L2 normalization over feature space can produce capable performance for Out-of-Distribution (OoD) detection for some models and datasets. Although it does not d…
cs.LG2022★ 2 cited
Linking Neural Collapse and L2 Normalization with Improved Out-of-Distribution Detection in Deep Neural Networks
Jarrod Haas, William Yolland, Bernhard Rabus
We propose a simple modification to standard ResNet architectures--L2 normalization over feature space--that substantially improves out-of-distribution (OoD) performance on the pre…