Publications

Below is a list of publications I have co-authored. For bibliometrics, see Google Scholar.

2021

Isometric Gaussian Process Latent Variable Model for Dissimilarity Data
Martin Jørgensen and Søren Hauberg.
International Conference on Machine Learning (ICML), 2021.
PDF arXiv

Automated Quantification of sTIL Density with H&E-Based Digital Image Analysis Has Prognostic Potential in Triple-Negative Breast Cancers
Jeppe Thagaard, Elisabeth S. Stovgaard, Line G. Vognsen, Søren Hauberg, Anders Dahl, Thomas Ebstrup, Johan Doré, Rikke E. Vincentz, Rikke K. Jepsen, Anne Roslind, Iben Kümler, Dorte Nielsen and Eva Balslev.
Cancers, 13(12), June 2021.
PDF Publishers site

Pulling back information geometry
Georgios Arvantidis, Miguel González-Duque, Alison Pouplin, Dimitris Kalatzis and Søren Hauberg.
arXiv preprint, 2021.
PDF arXiv

Spontaneous Symmetry Breakingin Data Visualization
Cilie W. Feldager, Søren Hauberg, and Lars Kai Hansen.
In International Conference on Artificial Neural Networks (ICANN), 2021.
PDF

Geometrically Enriched Latent Spaces
Georgios Arvanitidis, Søren Hauberg, and Bernhard Schölkopf.
Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS), 2021.
PDF arXiv

Hierarchical VAEs Know What They Don’t Know
Jakob D. Havtorn, Jes Frellsen, Søren Hauberg and Lars Maaløe.
International Conference on Machine Learning (ICML), 2021.
PDF arXiv

Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval
Frederik Warburg, Martin Jørgensen, Javier Civera and Søren Hauberg.
International Conference on Computer Vision (ICCV), 2021.
PDF arXiv

Multi-chart flows
Dimitris Kalatzis, Johan Ziruo Ye, Jesper Wohlert and Søren Hauberg.
arXiv preprint, 2021.
PDF arXiv

Learning Riemannian Manifolds for Geodesic Motion Skills
Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann and Leonel Rozo.
Robotics: Science and Systems (RSS), 2021.
PDF arXiv Best student paper award

Bounds all around: training energy-based models with bidirectional bounds
Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, and Søren Hauberg.
In Advances in Neural Information Processing Systems (NeurIPS) 34, 2021.
PDF arXiv

2020

Can you trust predictive uncertainty under real dataset shifts in digital pathology?
Jeppe Thagaard, Søren Hauberg, Bert van der Vegt, Thomas Ebstrup, Johan D. Hansen, and Anders B. Dahl.
In Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2020, Lima, Peru, October 2020.
PDF

What is a meaningful representation of protein sequences?
Nicki Skafte Detlefsen, Søren Hauberg and Wouter Boomsma.
Preprint, 2020.
PDF arXiv

Intrinsic Grassmann Averages for Online Linear Robust and Nonlinear Subspace Learning
Rudrasis Chakraborty, Liu Yang, Søren Hauberg and Baba C. Vemuri.
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
PDF

Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition
Frederik Warburg, Søren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, and Javier Civera.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2020
PDF Mapillary blog Dataset

Variational Autoencoders with Riemannian Brownian Motion Priors
Dimitris Kalatzis, David Eklund, Georgios Arvanitidis and Søren Hauberg.
In International Conference on Machine Learning (ICML), 2020.
PDF arXiv

Reparametrization Invariance in non-parametric Causal Discovery
Martin Jørgensen and Søren Hauberg.
arXiv preprint, 2020.
PDF arXiv

2019

Expected path length on random manifolds
David Eklund and Søren Hauberg.
arXiv preprint, 2019.
PDF arXiv

Parallel QR factorization of block-tridiagonal matrices
Alfredo Buttari, Søren Hauberg and Costy Kodsi.
SIAM Journal on Scientific Computing, 2020.
PDF Publishers site HAL

Reliable training and estimation of variance networks
Nicki Skafte Detlefsen, Martin Jørgensen, and Søren Hauberg.
In Advances in Neural Information Processing Systems (NeurIPS), 2019.
PDF arXiv

Fast and Robust Shortest Paths on Manifolds Learned from Data
Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, and Michael Schober.
In Proceedings of the 22nd international Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
PDF Supplements Code

Explicit Disentanglement of Appearance and Perspective in Generative Models
Nicki Skafte Detlefsen, and Søren Hauberg.
In Advances in Neural Information Processing Systems (NeurIPS), 2019.
PDF arXiv

Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models
Anton Mallasto, Søren Hauberg, and Aasa Feragen.
In Proceddings of 22nd international Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
PDF ArXiv

2018

Deep Diffeomorphic Transformer Networks
Nicki Skafte Detlefsen, Oren Freifeld and Søren Hauberg.
In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Salt Lake City, USA. July 2018.
PDF Code

Latent Space Oddity: on the Curvature of Deep Generative Models
Georgios Arvanitidis, Lars Kai Hansen and Søren Hauberg.
In International Conference on Learning Representations (ICLR), 2018.
PDF

Only Bayes should learn a manifold (on the estimation of differential geometric structure from data)
Søren Hauberg.
Unpublished manuscript, 2018.
PDF arXiv

Directional Statistics with the Spherical Normal Distribution
Søren Hauberg.
In Proceedings of FUSION 2018.
PDF Supplements

On the Geometry of Latent Variable Models
Søren Hauberg.
Oberwolfach abstract from Statistics for Data with Geometric Structure, 2018 (3).
PDF Workshop and complete report

Geodesic Clustering in Deep Generative Models
Tao Yang, Georgios Arvanitidis, Dongmei Fu, Xiaogang Li, and Søren Hauberg.
arXiv preprint, 2018.
PDF arXiv

The non-central Nakagami distribution
Søren Hauberg.
Unpublished technical note, 2018.
PDF

2017

Transformations Based on Continuous Piecewise-Affine Velocity Fields
Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich and John W. Fisher III.
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
PDF Supplements Derivative of gradient Code

Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning
Rudrasis Chakraborty, Søren Hauberg, and Baba C. Vemuri.
In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Honolulu, USA. July 2017.
PDF arXiv

Maximum likelihood estimation of Riemannian metrics from Euclidean data
Georgios Arvanitidis, Lars Kai Hansen and Søren Hauberg.
In Geometric Science of Information (GSI), 2017.
PDF

2016

Data-driven forward model inference for EEG brain imaging
Sofie Therese Hansen, Søren Hauberg, and Lars Kai Hansen.
In NeuroImage, 2016.
Publisher's site Preprint

Open Problem: Kernel methods on manifolds and metric spaces. What is the probability of a positive definite geodesic exponential kernel?
Aasa Feragen and Søren Hauberg.
In Conference on Learning Theory (COLT), 2016.
PDF Publisher's site

Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation
Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John W. Fisher III, and Lars Kai Hansen.
In Proceedings of the 19th international Conference on Artificial Intelligence and Statistics (AISTATS), volume 51, 2016.
PDF Publisher's site arXiv Animation Supplements

A Locally Adaptive Normal Distribution
Georgios Arvanitidis, Lars Kai Hansen, and Søren Hauberg.
Neural Information Processing Systems (NeurIPS), 2016.
PDF Errata arXiv YouTube

2015

A Random Riemannian Metric for Probabilistic Shortest-Path Tractography
Søren Hauberg, Michael Schober, Matthew Liptrot, Philipp Hennig, and Aasa Feragen.
In Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2015, Munich, Germany, September 2015.
PDF Youtube

Highly-Expressive Spaces of Well-Behaved Transformations: Keeping It Simple
Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich and John W. Fisher III.
In International Conference on Computer Vision (ICCV), Santiago, Chile. December 2015.
PDF Code

Principal Curves on Riemannian Manifolds
Søren Hauberg.
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
PDF Publishers site Supplements Animation

Geodesic Exponential Kernels: When Curvature and Linearity Conflict
Aasa Feragen,Françous Lauze, and Søren Hauberg.
In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Boston, USA. June 2015.
PDF Extended abstract (PDF) SIMBAD extended abstract (PDF) arXiv

Scalable Robust Principal Component Analysis using Grassmann Averages
Søren Hauberg, Aasa Feragen, Raffi Enficiaud and Michael J. Black.
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
PDF Publishers site Supplements Paper site w. code

2014

Metrics for Probabilistic Geometries
Alessandra Tosi, Søren Hauberg, Alfredo Vellido, and Neil D. Lawrence.
In The Conference on Uncertainty in Artificial Intelligence (UAI), Quebec, Canada. July 2014.
PDF arXiv

Probabilistic shortest path tractography in DTI using Gaussian Process ODE solvers
Michael Schober, Niklas Kasenburg, Aasa Feragen, Philipp Hennig, and Søren Hauberg.
In Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2014, Boston, USA, September 2014.
PDF Supplementary material Paper site w. code Youtube 1 Youtube 2

Model Transport: Towards Scalable Transfer Learning on Manifolds
Oren Freifeld, Søren Hauberg, and Michael J. Black.
In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA. June 2014.
PDF Supplementary material

Grassmann Averages for Scalable Robust PCA
Søren Hauberg, Aasa Feragen, and Michael J. Black.
In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Columbus, Ohio, USA. June 2014.
PDF Paper site w. code Tutorial video Results video Supplementary materials CVPR talk (video)

Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics
Philipp Hennig and Søren Hauberg.
In Proceedings of the 17th international Conference on Artificial Intelligence and Statistics (AISTATS), volume 33, 2014.
PDF Paper site w. code Youtube Supplements

2013

Unscented Kalman Filtering on Riemannian Manifolds
Søren Hauberg, Françous Lauze, and Kim S. Pedersen.
Journal of Mathematical Imaging and Vision, 46(1):103-120, May 2013.
PDF Publishers site Errata

2012

HUMIM Software for Articulated Tracking
Søren Hauberg and Kim S. Pedersen.
Technical Report 01/2012, Department of Computer Science, University of Copenhagen, January 2012.
PDF

A Geometric Take on Metric Learning
Søren Hauberg, Oren Freifeld, and Michael J. Black.
In Advances in Neural Information Processing Systems (NeurIPS) 25, MIT Press, pages 2033-2041, 2012.
PDF Supplementary material Code Poster

A geometric framework for statistics on trees
Aasa Feragen, Mads Nielsen, Søren Hauberg, Pechin Lo, Marleen de Bruijne, and Françous Lauze.
Technical Report 11/02, Department of Computer Science, University of Copenhagen, January 2012.
PDF

Natural Metrics and Least-Committed Priors for Articulated Tracking
Søren Hauberg, Stefan Sommer, and Kim S. Pedersen.
Image and Vision Computing, 30(6-7):453-461, 2012.
PDF Code Publishers site

Spatial Measures between Human Poses for Classification and Understanding
Søren Hauberg and Kim S. Pedersen.
In In Articulated Motion and Deformable Objects, Springer Berlin Heidelberg, volume 7378, LNCS, pages 26-36, 2012.
Publishers site

2011

An Empirical Study on the Performance of Spectral Manifold Learning Techniques
Peter Mysling, Søren Hauberg and Kim S. Pedersen.
In Artificial Neural Networks and Machine Learning - ICANN 2011, Springer Berlin Heidelberg, volume 6791, Lecture Notes in Computer Science, pages 347-354, 2011.
PDF

Unscented Kalman Filtering for Articulated Human Tracking
Anders B.L. Larsen, Søren Hauberg, and Kim S. Pedersen.
In Image Analysis, Springer Berlin Heidelberg, volume 6688, Lecture Notes in Computer Science, pages 228-237, 2011.
PDF Publishers site

A Physically Natural Metric for Human Motion and the Associated Brownian Motion Model
Søren Hauberg and Kim S. Pedersen.
In 1st IEEE Workshop on Kernels and Distances for Computer Vision (ICCV workshop), 2011.
Workshop site

Data-Driven Importance Distributions for Articulated Tracking
Søren Hauberg and Kim S. Pedersen.
In Energy Minimization Methods in Computer Vision and Pattern Recognition, Springer Berlin Heidelberg, volume 6819, Lecture Notes in Computer Science, pages 287-299, 2011.
PDF Errata Code

Predicting Articulated Human Motion from Spatial Processes
Søren Hauberg and Kim S. Pedersen.
International Journal of Computer Vision (IJCV), 2011.
PDF Paper site Code Publishers site

Means in spaces of tree-like shapes
Aasa Feragen, Søren Hauberg, Mads Nielsen, and Françous Lauze.
In IEEE International Conference on Computer Vision (ICCV), pages 736 -746, 2011.
PDF Supplementary material

Spatial Models of Human Motion
Søren Hauberg.
PhD thesis. University of Copenhagen, 2011.

2010

Gaussian-like Spatial Priors for Articulated Tracking
Søren Hauberg, Stefan Sommer, and Kim S. Pedersen.
In Computer Vision - ECCV 2010, Springer Berlin Heidelberg, volume 6311, Lecture Notes in Computer Science, pages 425-437, 2010.
PDF Errata Paper site Code Publishers site

Dense Marker-less Three Dimensional Motion Capture
Søren Hauberg, Bente R. Jensen, Morten Engell-Nørregård, Kenny Erleben, and Kim S. Pedersen.
In Virtual Vistas; Eleventh International Symposium on the 3D Analysis of Human Movement, 2010.

Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations
Stefan Sommer, Françous Lauze, Søren Hauberg, and Mads Nielsen.
In Computer Vision - ECCV 2010, Springer Berlin Heidelberg, volume 6316, pages 43-56, 2010.
PDF Publishers site

GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking
Rune M. Friborg, Søren Hauberg, and Kenny Erleben.
In The CVGPU workshop at European Conference on Computer Vision (ECCV) 2010.
PDF

Stick It! Articulated Tracking using Spatial Rigid Object Priors
Søren Hauberg and Kim S. Pedersen.
In Computer Vision - ACCV 2010, Springer Berlin Heidelberg, volume 6494, Lecture Notes in Computer Science, pages 758-769, 2010
PDF Errata Paper site Code Publishers site

2009

Interactive Inverse Kinematics for Monocular Motion Estimation
Morten Engell-Nørregård, Søren Hauberg, Jerome Lapuyade,Kenny Erleben, and Kim S. Pedersen.
In The 6th Workshop on Virtual Reality Interaction and Physical Simulation (VRIPHYS), 2009.
Conference site Paper site

Three Dimensional Monocular Human Motion Analysis in End-Effector Space
Søren Hauberg, Jerome Lapuyade, Morten Engell-Nørregård, Kenny Erleben, and Kim S. Pedersen.
In Energy Minimization Methods in Computer Vision and Pattern Recognition, Springer Berlin Heidelberg, volume 5681, Lecture Notes in Computer Science, pages 235-248, 2009.
PDF Paper site Publishers site

2008

Brownian Warps for Non-Rigid Registration
Mads Nielsen, Peter Johansen, Andrew Jackson, Benny Lautrup, and Søren Hauberg.
Journal of Mathematical Imaging and Vision, 2008.
PDF Publishers site

An Efficient Algorithm for Modelling Duration in Hidden Markov Models, with a Dramatic Application
Søren Hauberg and Jakob Sloth.
Journal of Mathematical Imaging and Vision, 2008.
PDF Paper site Publishers site

GNU Octave Manual Version 3
John W. Eaton, David Bateman, and Søren Hauberg.
Network Theory Ltd., 2008.
Publishers site GNU Octave