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cs.LG2021
FRuDA: Framework for Distributed Adversarial Domain Adaptation
Shaoduo Gan, Akhil Mathur, Anton Isopoussu +3
Breakthroughs in unsupervised domain adaptation (uDA) can help in adapting models from a label-rich source domain to unlabeled target domains. Despite these advancements, there is…
cs.LG2021★ 2 cited
Deep Inertial Navigation using Continuous Domain Adaptation and Optimal Transport
Mohammed Alloulah, Maximilian Arnold, Anton Isopoussu
In this paper, we propose a new strategy for learning inertial robotic navigation models. The proposed strategy enhances the generalisability of end-to-end inertial modelling, and…