3 citations · 6 across the 4 of their papers we have counts for
4 papers
NECO: NEural Collapse Based Out-of-distribution detection
Mouïn Ben Ammar, Nacim Belkhir, Sebastian Popescu +2
Detecting out-of-distribution (OOD) data is a critical challenge in machine learning due to model overconfidence, often without awareness of their epistemological limits. We hypoth…
Distributional Gaussian Processes Layers for Out-of-Distribution Detection
Sebastian G. Popescu, David J. Sharp, James H. Cole +2
Machine learning models deployed on medical imaging tasks must be equipped with out-of-distribution detection capabilities in order to avoid erroneous predictions. It is unsure whe…
Distributional Gaussian Process Layers for Outlier Detection in Image Segmentation
Sebastian G. Popescu, David J. Sharp, James H. Cole +2
We propose a parameter efficient Bayesian layer for hierarchical convolutional Gaussian Processes that incorporates Gaussian Processes operating in Wasserstein-2 space to reliably…
Hierarchical Gaussian Processes with Wasserstein-2 Kernels
Sebastian Popescu, David Sharp, James Cole +1
Stacking Gaussian Processes severely diminishes the model's ability to detect outliers, which when combined with non-zero mean functions, further extrapolates low non-parametric va…