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Ole E. Barndorff-Nielsen: Sand, Wind and Inference
Michael S{\o}rensen
https://arxiv.org/abs/2506.14389 https://arxiv.org/pdf/2506.14…

Ole E. Barndorff-Nielsen: Sand, Wind and Inference
This paper reviews Ole Eiler Barndorff-Nielsen's research in the first decades of his career. The focus is on topics that he kept returning to throughout his scientific life, and on papers that he built on in later important contributions. First his early contributions to the foundations of statistical inference are reviewed with focus on conditional inference and exponential families, two topics in which he had a lifelong interest. The second half of the paper reviews his research on wind blow…

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning
Asbj{\o}rn Munk, Stefano Cerri, Jakob Ambsdorf, Julia Machnio, Sebastian N{\o}rgaard Llambias, Vardan Nersesjan, Christian Hedeager Krag, Peirong Liu, Pablo Rocamora Garc\'ia, Mostafa Mehdipour Ghazi, Mikael Boesen, Michael Eriksen Benros, Juan Eugenio Iglesias, Mads Nielsen

A large-scale heterogeneous 3D magnetic resonance brain imaging dataset for self-supervised learning
We present FOMO60K, a large-scale, heterogeneous dataset of 60,529 brain Magnetic Resonance Imaging (MRI) scans from 13,900 sessions and 11,187 subjects, aggregated from 16 publicly available sources. The dataset includes both clinical- and research-grade images, multiple MRI sequences, and a wide range of anatomical and pathological variability, including scans with large brain anomalies. Minimal preprocessing was applied to preserve the original image characteristics while reducing barriers t…