3 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Covariance Last-Layer Ensembles: Function-Space Diversity for Efficient Uncertainty Quantification
H. Martin Gillis, Isaac Xu, Gabriel Spadon +1
A Last-Layer Ensemble (LLE), linear units on one shared frozen feature map, is an efficient single-pass approach to the disagreement-based epistemic uncertainty for out-of-dist…
cs.CV2024★ 3 cited
Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat Imagery
Isaac Xu, Benjamin Misiuk, Scott C. Lowe +3
In this work, we apply state-of-the-art self-supervised learning techniques on a large dataset of seafloor imagery, \textit{BenthicNet}, and study their performance for a complex h…
cs.LG2024
Label-free Monitoring of Self-Supervised Learning Progress
Isaac Xu, Scott Lowe, Thomas Trappenberg
Self-supervised learning (SSL) is an effective method for exploiting unlabelled data to learn a high-level embedding space that can be used for various downstream tasks. However, e…