5 citations · 10 across the 9 of their papers we have counts for
Showing 2023Show all
2 papers · 1 filter
cs.DC2023★ 1 cited
fmiSwap: Run-time Swapping of Models for Co-simulation and Digital Twins
Henrik Ejersbo, Kenneth Lausdahl, Mirgita Frasheri +1
Digital Twins represent a new and disruptive technology, where digital replicas of (cyber)-physical systems operate for long periods of time alongside their (cyber)-physical counte…
cs.LG2023★ 5 cited
Adaptive Parameterization of Deep Learning Models for Federated Learning
Morten From Elvebakken, Alexandros Iosifidis, Lukas Esterle
Federated Learning offers a way to train deep neural networks in a distributed fashion. While this addresses limitations related to distributed data, it incurs a communication over…