110 citations · 334 across the 37 of their papers we have counts for
3 papers · 1 filter
Probabilistic Sampling of Balanced K-Means using Adiabatic Quantum Computing
Jan-Nico Zaech, Martin Danelljan, Tolga Birdal +1
Adiabatic quantum computing (AQC) is a promising approach for discrete and often NP-hard optimization problems. Current AQCs allow to implement problems of research interest, which…
How Reliable is Your Regression Model's Uncertainty Under Real-World Distribution Shifts?
Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
Many important computer vision applications are naturally formulated as regression problems. Within medical imaging, accurate regression models have the potential to automate vario…
Learning Proposals for Practical Energy-Based Regression
Fredrik K. Gustafsson, Martin Danelljan, Thomas B. Schön
Energy-based models (EBMs) have experienced a resurgence within machine learning in recent years, including as a promising alternative for probabilistic regression. However, energy…