Publications

2024

Pre-prints and additional publications:

2023

Peer-reviewed:

  • Philipp Harms, Peter W. Michor, Xavier Pennec, Stefan Sommer: Geometry of sample spaces, in: Differential Geometry and its Applications, Volume 90, October 2023
  • Benjamin Eltzner, Pernille E. H. Hansen, Stephan Huckemann, Stefan Sommer: Diffusion Means in Geometric Spaces, in: Bernoulli papers
  • Akhøj M, Pennec X, Sommer S. (2023). Tangent Phylogenetic PCA. Image Analysis – 22nd Scandinavian Conference, SCIA 2023, Sirkka, Finland, April 18–21, 2023, Proceedings, Part II  (pp. 77-90). Springer Nature Switzerland.
  • Baker E, Besnier T, Sommer S. (2023). A Function Space Perspective on Stochastic Shape Evolution. Image Analysis – 22nd Scandinavian Conference, SCIA 2023, Sirkka, Finland, April 18–21, 2023, Proceedings, Part II  (pp. 278-292). Springer Nature Switzerland.

Pre-prints:

  • Chao Zhang; Rasmus Nielsen; Siavash Mirarab: inference from whole-genome alignments, 10.1101/2023.10.04.560884
  • Gefan Yang, Stefan Sommer: A Denoising Diffusion Model for Fluid Field Prediction (arxiv), accepted for NeurIPS workshop
  • Liwei Hu, Wenyong Wang, University of Electronic Science and Technology of China; Yu Xiang, University of Electronic Science and Technology of China, Sommer, Stefan, University of Copenhagen: Incorporating Riemannian Geometric Features for Learning Coefficient of Pressure Distributions on Airplane Wings. Submitted for IEEE transcations on Aerodynamics and Electronic System
  • Morten Akhøj, James Benn, Erlend Grong, Stefan Sommer, Xavier Pennec: Principal subbundles for dimension reduction, paper under review

Additional publications:

  • Karl Levinsen & Thomas Schrum Nicolet: Domain-specific Diffusion in the Butterfly Domain, MSc Thesis, Computer Science, 29-05-2023. Supervisor: Stefan H. Sommer
  • Hu, L. (2023). Research on Deep Learning Method for Joint Modeling of Aerodynamic Layout and Flight Status Features (PhD thesis)
  • Gefan Yang: “A Denoising Diffusion Model for Synthetic Fluid Field Prediction” (MSc thesis)
  • Morten A Pedersen: Riemannian and sub-Riemannian methods for dimension reduction (PhD thesis)

Media coverage:

2022

Peer-reviewed:

Pre-prints and additional publications: