3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.CL2023
Neural machine translation for automated feedback on children's early-stage writing
Jonas Vestergaard Jensen, Mikkel Jordahn, Michael Riis Andersen
In this work, we address the problem of assessing and constructing feedback for early-stage writing automatically using machine learning. Early-stage writing is typically vastly di…
stat.ML2023★ 3 cited
On the role of Model Uncertainties in Bayesian Optimization
Jonathan Foldager, Mikkel Jordahn, Lars Kai Hansen +1
Bayesian optimization (BO) is a popular method for black-box optimization, which relies on uncertainty as part of its decision-making process when deciding which experiment to perf…