33 citations · 182 across the 20 of their papers we have counts for
22 papers
SE-MSB: End-to-End Unpaired Speech Enhancement using Mamba Schrödinger Bridges
Andreas Bagge, Andreas Nymand, Michael Riis Andersen +1
Speech enhancement (SE) models typically rely on supervised learning with paired data examples where clean speech is synthetically degraded. This paradigm limits performance in rea…
Polygonizer: An auto-regressive building delineator
Maxim Khomiakov, Michael Riis Andersen, Jes Frellsen
In geospatial planning, it is often essential to represent objects in a vectorized format, as this format easily translates to downstream tasks such as web development, graphics, o…
Learning to Generate 3D Representations of Building Roofs Using Single-View Aerial Imagery
Maxim Khomiakov, Alejandro Valverde Mahou, Alba Reinders Sánchez +2
We present a novel pipeline for learning the conditional distribution of a building roof mesh given pixels from an aerial image, under the assumption that roof geometry follows a s…
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…
SolarDK: A high-resolution urban solar panel image classification and localization dataset
Maxim Khomiakov, Julius Holbech Radzikowski, Carl Anton Schmidt +4
The body of research on classification of solar panel arrays from aerial imagery is increasing, yet there are still not many public benchmark datasets. This paper introduces two no…
A Framework for Improving the Reliability of Black-box Variational Inference
Manushi Welandawe, Michael Riis Andersen, Aki Vehtari +1
Black-box variational inference (BBVI) now sees widespread use in machine learning and statistics as a fast yet flexible alternative to Markov chain Monte Carlo methods for approxi…