1 citations · 1 across the 6 of their papers we have counts for
3 papers · 1 filter
Streamlining Prediction in Bayesian Deep Learning
Rui Li, Marcus Klasson, Arno Solin +1
The rising interest in Bayesian deep learning (BDL) has led to a plethora of methods for estimating the posterior distribution. However, efficient computation of inferences, such a…
Privacy Leakage via Output Label Space and Differentially Private Continual Learning
Marlon Tobaben, Talal Alrawajfeh, Marcus Klasson +3
Differential privacy (DP) is a formal privacy framework that enables training machine learning (ML) models while protecting individuals' data. As pointed out by prior work, ML mode…
Flatness Improves Backbone Generalisation in Few-shot Classification
Rui Li, Martin Trapp, Marcus Klasson +1
Deployment of deep neural networks in real-world settings typically requires adaptation to new tasks with few examples. Few-shot classification (FSC) provides a solution to this pr…