Mikkel Jordahn

12 papers A* 2A 2Journal 7Unranked 1
YearRankTypeTitle / Venue / Authors
2026 J jnl
Practical Deep Heteroskedastic Regression.
CoRR
Mikkel Jordahn, Jonas Vestergaard Jensen, James Harrison, Michael Riis Andersen, Mikkel N. Schmidt
2025 A* conf
Bayesian Optimization via Continual Variational Last Layer Training.
ICLR
Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison
2025 A conf
On Local Posterior Structure in Deep Ensembles.
AISTATS
Mikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen
2025 J jnl
On Local Posterior Structure in Deep Ensembles.
CoRR
Mikkel Jordahn, Jonas Vestergaard Jensen, Mikkel N. Schmidt, Michael Riis Andersen
2024 J jnl
Bayesian Optimization via Continual Variational Last Layer Training.
CoRR
Paul Brunzema, Mikkel Jordahn, John Willes, Sebastian Trimpe, Jasper Snoek, James Harrison
2024 A* conf
Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks.
ICML
Mikkel Jordahn, Pablo M. Olmos
2024 J jnl
Decoupling Feature Extraction and Classification Layers for Calibrated Neural Networks.
CoRR
Mikkel Jordahn, Pablo M. Olmos
2024 — conf
Neural machine translation for automated feedback on children's early-stage writing.
NLDL
Jonas Vestergaard Jensen, Mikkel Jordahn, Michael Riis Andersen
2023 J jnl
Neural machine translation for automated feedback on children's early-stage writing.
CoRR
Jonas Vestergaard Jensen, Mikkel Jordahn, Michael Riis Andersen
2023 J jnl
On the role of Model Uncertainties in Bayesian Optimization.
CoRR
Jonathan Foldager, Mikkel Jordahn, Lars Kai Hansen, Michael Riis Andersen
2023 A conf
On the role of model uncertainties in Bayesian optimisation.
UAI
Jonathan Foldager, Mikkel Jordahn, Lars Kai Hansen, Michael Riis Andersen
2021 J jnl
Topic Model Robustness to Automatic Speech Recognition Errors in Podcast Transcripts.
CoRR
Raluca Alexandra Fetic, Mikkel Jordahn, Lucas Chaves Lima, Rasmus Arpe Fogh Egebæk, Martin Carsten Nielsen, Benjamin Biering, Lars Kai Hansen