8 citations · 8 across the 3 of their papers we have counts for
3 papers
FlexMoRE: A Flexible Mixture of Rank-heterogeneous Experts for Efficient Federatedly-trained Large Language Models
Annemette Brok Pirchert, Jacob Nielsen, Mogens Henrik From +2
Recent advances in mixture-of-experts architectures have shown that individual experts models can be trained federatedly, i.e., in isolation from other experts by using a common ba…
DeToNATION: Decoupled Torch Network-Aware Training on Interlinked Online Nodes
Mogens Henrik From, Jacob Nielsen, Lukas Galke Poech +1
Training large neural network models requires extensive computational resources, often distributed across several nodes and accelerators. Recent findings suggest that it may be suf…
A Cusp-Core like challenge for Modified Newtonian Dynamics
Mikkel H. Eriksen, Mads T. Frandsen, Mogens H. From
We show that Modified Newtonian Dynamics (MOND) predict distinct galactic acceleration curve geometries in -space - the space of total observed centripetal accelerations $g_{\r…