Søren Hauberg

156 papers A* 30A 13C 2Journal 87Unranked 24

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Extended neural contractive dynamical systems: On multiple tasks and Riemannian safety regions. Int. J. Robotics Res. Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
2025	—	`conf`	Are Generative Models Fair? A Study of Racial Bias in Dermatological Image Generation. SCIA (2) Miguel López-Pérez, Søren Hauberg, Aasa Feragen
2025	J	`jnl`	Are generative models fair? A study of racial bias in dermatological image generation. CoRR Miguel López-Pérez, Søren Hauberg, Aasa Feragen
2025	A	`conf`	Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections. AISTATS Marco Miani, Hrittik Roy, Søren Hauberg
2025	J	`jnl`	Bayesian generative models can flag performance loss, bias, and out-of-distribution image content. CoRR Miguel López-Pérez, Marco Miani, Valery Naranjo, Søren Hauberg, Aasa Feragen
2025	J	`jnl`	Beyond Quantification: Navigating Uncertainty in Professional AI Systems. CoRR Sylvie Delacroix, Diana Robinson, Umang Bhatt, Jacopo Domenicucci, Jessica Montgomery, Gaël Varoquaux, Carl Henrik Ek, Vincent Fortuin, Yulan He, Tom Diethe, Neill W. Campbell, Mennatallah El-Assady, Søren Hauberg, Ivana Dusparic, Neil D. Lawrence
2025	J	`jnl`	Connecting Neural Models Latent Geometries with Relative Geodesic Representations. CoRR Hanlin Yu, Berfin Inal, Georgios Arvanitidis, Søren Hauberg, Francesco Locatello, Marco Fumero
2025	J	`jnl`	Contact Wasserstein Geodesics for Non-Conservative Schrödinger Bridges. CoRR Andrea Testa, Søren Hauberg, Tamim Asfour, Leonel Rozo
2025	J	`jnl`	Exploring Bidirectional Bounds for Minimax-Training of Energy-Based Models. Int. J. Comput. Vis. Cong Geng, Jia Wang, Li Chen, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2025	J	`jnl`	Exploring bidirectional bounds for minimax-training of Energy-based models. CoRR Cong Geng, Jia Wang, Li Chen, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2025	A*	`conf`	Geometric Contact Flows: Contactomorphisms for Dynamics and Control. ICML Andrea Testa, Søren Hauberg, Tamim Asfour, Leonel Rozo
2025	J	`jnl`	Geometric Contact Flows: Contactomorphisms for Dynamics and Control. CoRR Andrea Testa, Søren Hauberg, Tamim Asfour, Leonel Rozo
2025	A*	`conf`	Identifying Metric Structures of Deep Latent Variable Models. ICML Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg
2025	J	`jnl`	Identifying metric structures of deep latent variable models. CoRR Stas Syrota, Yevgen Zainchkovskyy, Johnny Xi, Benjamin Bloem-Reddy, Søren Hauberg
2025	J	`jnl`	Learning geometry and topology via multi-chart flows. CoRR Hanlin Yu, Søren Hauberg, Marcelo Hartmann, Arto Klami, Georgios Arvanitidis
2025	J	`jnl`	Likely Interpolants of Generative Models. CoRR Frederik Möbius Rygaard, Shen Zhu, Yinzhu Jin, Søren Hauberg, Tom Fletcher
2025	J	`jnl`	Matrix-Free Least Squares Solvers: Values, Gradients, and What to Do With Them. CoRR Hrittik Roy, Søren Hauberg, Nicholas Krämer
2025	A	`conf`	Riemann AISTATS Leonel Rozo, Miguel González Duque, Noémie Jaquier, Søren Hauberg
2025	J	`jnl`	Riemann CoRR Leonel Rozo, Miguel González Duque, Noémie Jaquier, Søren Hauberg
2025	J	`jnl`	Riemannian generative decoder. CoRR Andreas Bjerregaard, Søren Hauberg, Anders Krogh
2025	J	`jnl`	Spacetime Geometry of Denoising in Diffusion Models. CoRR Rafal Karczewski, Markus Heinonen, Alison Pouplin, Søren Hauberg, Vikas Garg
2025	J	`jnl`	VIKING: Deep variational inference with stochastic projections. CoRR Samuel G. Fadel, Hrittik Roy, Nicholas Krämer, Yevgen Zainchkovskyy, Stas Syrota, Alejandro Valverde Mahou, Carl Henrik Ek, Søren Hauberg
2024	J	`jnl`	A Continuous Relaxation for Discrete Bayesian Optimization. CoRR Richard Michael, Simon Bartels, Miguel González Duque, Yevgen Zainchkovskyy, Jes Frellsen, Søren Hauberg, Wouter Boomsma
2024	A*	`conf`	A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences. NeurIPS Miguel González Duque, Richard Michael, Simon Bartels, Yevgen Zainchkovskyy, Søren Hauberg, Wouter Boomsma
2024	J	`jnl`	A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences. CoRR Miguel González Duque, Richard Michael, Simon Bartels, Yevgen Zainchkovskyy, Søren Hauberg, Wouter Boomsma
2024	A	`conf`	Accurate Computation of the Logarithm of Modified Bessel Functions on GPUs. ICS Andreas Plesner, Hans Henrik Brandenborg Sørensen, Søren Hauberg
2024	J	`jnl`	Accurate Computation of the Logarithm of Modified Bessel Functions on GPUs. CoRR Andreas Plesner, Hans Henrik Brandenborg Sørensen, Søren Hauberg
2024	J	`jnl`	Bayes without Underfitting: Fully Correlated Deep Learning Posteriors via Alternating Projections. CoRR Marco Miani, Hrittik Roy, Søren Hauberg
2024	—	`conf`	Decoder ensembling for learned latent geometries. GRaM Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg
2024	J	`jnl`	Decoder ensembling for learned latent geometries. CoRR Stas Syrota, Pablo Moreno-Muñoz, Søren Hauberg
2024	J	`jnl`	Extended Neural Contractive Dynamical Systems: On Multiple Tasks and Riemannian Safety Regions. CoRR Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
2024	A*	`conf`	Gradients of Functions of Large Matrices. NeurIPS Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg
2024	J	`jnl`	Gradients of Functions of Large Matrices. CoRR Nicholas Krämer, Pablo Moreno-Muñoz, Hrittik Roy, Søren Hauberg
2024	A*	`conf`	Improving Adversarial Energy-Based Model via Diffusion Process. ICML Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li
2024	J	`jnl`	Improving Adversarial Energy-Based Model via Diffusion Process. CoRR Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, Bo Li
2024	—	`conf`	Laplacian Segmentation Networks Improve Epistemic Uncertainty Quantification. MICCAI (8) Kilian Zepf, Selma Wanna, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Frederik Warburg, Aasa Feragen
2024	A*	`conf`	Neural Contractive Dynamical Systems. ICLR Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo
2024	J	`jnl`	Neural Contractive Dynamical Systems. CoRR Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Nadia Figueroa, Gerhard Neumann, Leonel Rozo
2024	A*	`conf`	Reparameterization invariance in approximate Bayesian inference. NeurIPS Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg
2024	J	`jnl`	Reparameterization invariance in approximate Bayesian inference. CoRR Hrittik Roy, Marco Miani, Carl Henrik Ek, Philipp Hennig, Marvin Pförtner, Lukas Tatzel, Søren Hauberg
2024	A*	`conf`	Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information. NeurIPS Marco Miani, Lorenzo Beretta, Søren Hauberg
2024	J	`jnl`	Sketched Lanczos uncertainty score: a low-memory summary of the Fisher information. CoRR Marco Miani, Lorenzo Beretta, Søren Hauberg
2024	J	`jnl`	Variational Autoencoding of Dental Point Clouds. Trans. Mach. Learn. Res. Johan Ziruo Ye, Thomas Ørkild, Peter Lempel Søndergard, Søren Hauberg
2024	—	`conf`	Visualizing Riemannian data with Rie-SNE. MLVis@EuroVis Andri Bergsson, Søren Hauberg
2023	A	`conf`	Adaptive Cholesky Gaussian Processes. AISTATS Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg
2023	A*	`conf`	Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval. NeurIPS Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg
2023	J	`jnl`	Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval. CoRR Frederik Warburg, Marco Miani, Silas Brack, Søren Hauberg
2023	J	`jnl`	Identifying latent distances with Finslerian geometry. Trans. Mach. Learn. Res. Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg
2023	J	`jnl`	Laplacian Segmentation Networks: Improved Epistemic Uncertainty from Spatial Aleatoric Uncertainty. CoRR Kilian Zepf, Selma Wanna, Marco Miani, Juston Moore, Jes Frellsen, Søren Hauberg, Aasa Feragen, Frederik Warburg
2023	A*	`conf`	Learning to Taste: A Multimodal Wine Dataset. NeurIPS Thoranna Bender, Simon Møe Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, Søren Hauberg, Serge J. Belongie, Frederik Warburg
2023	J	`jnl`	Learning to Taste: A Multimodal Wine Dataset. CoRR Thoranna Bender, Simon Møe Sørensen, Alireza Kashani, Kristjan Eldjarn Hjorleifsson, Grethe Hyldig, Søren Hauberg, Serge J. Belongie, Frederik Warburg
2023	A*	`conf`	On Masked Pre-training and the Marginal Likelihood. NeurIPS Pablo Moreno-Muñoz, Pol Garcia Recasens, Søren Hauberg
2023	J	`jnl`	On Masked Pre-training and the Marginal Likelihood. CoRR Pablo Moreno-Muñoz, Pol G. Recasens, Søren Hauberg
2023	J	`jnl`	Reactive motion generation on learned Riemannian manifolds. Int. J. Robotics Res. Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Rozo
2023	A*	`conf`	Riemannian Laplace approximations for Bayesian neural networks. NeurIPS Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis
2023	J	`jnl`	Riemannian Laplace approximations for Bayesian neural networks. CoRR Federico Bergamin, Pablo Moreno-Muñoz, Søren Hauberg, Georgios Arvanitidis
2023	J	`jnl`	Variational Point Encoding Deformation for Dental Modeling. CoRR Johan Ziruo Ye, Thomas Ørkild, Peter Lempel Søndergaard, Søren Hauberg
2022	J	`jnl`	Adaptive Cholesky Gaussian Processes. CoRR Simon Bartels, Kristoffer Stensbo-Smidt, Pablo Moreno-Muñoz, Wouter Boomsma, Jes Frellsen, Søren Hauberg
2022	J	`jnl`	Benchmarking Generative Latent Variable Models for Speech. CoRR Jakob D. Havtorn, Lasse Borgholt, Søren Hauberg, Jes Frellsen, Lars Maaløe
2022	J	`jnl`	Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization. CoRR Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera
2022	J	`jnl`	Danish Airs and Grounds: A Dataset for Aerial-to-Street-Level Place Recognition and Localization. IEEE Robotics Autom. Lett. Andrea Vallone, Frederik Warburg, Hans Hansen, Søren Hauberg, Javier Civera
2022	—	`conf`	ICLR 2022 Challenge for Computational Geometry & Topology: Design and Results. TAG-ML Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane
2022	J	`jnl`	ICLR 2022 Challenge for Computational Geometry and Topology: Design and Results. CoRR Adele Myers, Saiteja Utpala, Shubham Talbar, Sophia Sanborn, Christian Shewmake, Claire Donnat, Johan Mathe, Umberto Lupo, Rishi Sonthalia, Xinyue Cui, Tom Szwagier, Arthur Pignet, Andri Bergsson, Søren Hauberg, Dmitriy Nielsen, Stefan Sommer, David A. Klindt, Erik Hermansen, Melvin Vaupel, Benjamin A. Dunn, Jeffrey Xiong, Noga Aharony, Itsik Pe'er, Felix Ambellan, Martin Hanik, Esfandiar Nava-Yazdani, Christoph von Tycowicz, Nina Miolane
2022	J	`jnl`	Identifying latent distances with Finslerian geometry. CoRR Alison Pouplin, David Eklund, Carl Henrik Ek, Søren Hauberg
2022	J	`jnl`	Is an encoder within reach? CoRR Helene Hauschultz, Rasmus Berg Palm, Pablo Moreno-Muños, Nicki Skafte Detlefsen, Andrew Allan du Plessis, Søren Hauberg
2022	A*	`conf`	Laplacian Autoencoders for Learning Stochastic Representations. NeurIPS Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte Detlefsen, Søren Hauberg
2022	J	`jnl`	Laplacian Autoencoders for Learning Stochastic Representations. CoRR Marco Miani, Frederik Warburg, Pablo Moreno-Muñoz, Nicki Skafte Detlefsen, Søren Hauberg
2022	C	`conf`	Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry. CoG Miguel González Duque, Rasmus Berg Palm, Søren Hauberg, Sebastian Risi
2022	J	`jnl`	Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry. CoRR Miguel González Duque, Rasmus Berg Palm, Søren Hauberg, Sebastian Risi
2022	A	`conf`	Model-agnostic out-of-distribution detection using combined statistical tests. AISTATS Federico Bergamin, Pierre-Alexandre Mattei, Jakob Drachmann Havtorn, Hugo Sénétaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
2022	J	`jnl`	Model-agnostic out-of-distribution detection using combined statistical tests. CoRR Federico Bergamin, Pierre-Alexandre Mattei, Jakob D. Havtorn, Hugo Senetaire, Hugo Schmutz, Lars Maaløe, Søren Hauberg, Jes Frellsen
2022	A	`conf`	Probabilistic spatial transformer networks. UAI Pola Schwöbel, Frederik Rahbæk Warburg, Martin Jørgensen, Kristoffer Hougaard Madsen, Søren Hauberg
2022	J	`jnl`	Probabilistic thermal stability prediction through sparsity promoting transformer representation. CoRR Yevgen Zainchkovskyy, Jesper Ferkinghoff-Borg, Anja Bennett, Thomas Egebjerg, Nikolai Lorenzen, Per Greisen Jr., Søren Hauberg, Carsten Stahlhut
2022	A	`conf`	Pulling back information geometry. AISTATS Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitrios Kalatzis, Søren Hauberg
2022	J	`jnl`	Reactive Motion Generation on Learned Riemannian Manifolds. CoRR Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo
2022	A*	`conf`	Revisiting Active Sets for Gaussian Process Decoders. NeurIPS Pablo Moreno-Muñoz, Cilie W. Feldager, Søren Hauberg
2022	J	`jnl`	Revisiting Active Sets for Gaussian Process Decoders. CoRR Pablo Moreno-Muñoz, Cilie W. Feldager, Søren Hauberg
2022	J	`jnl`	Robust uncertainty estimates with out-of-distribution pseudo-inputs training. CoRR Pierre Segonne, Yevgen Zainchkovskyy, Søren Hauberg
2022	J	`jnl`	Visualizing Riemannian data with Rie-SNE. CoRR Andri Bergsson, Søren Hauberg
2021	A*	`conf`	Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. ICCV Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
2021	A*	`conf`	Bounds all around: training energy-based models with bidirectional bounds. NeurIPS Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2021	J	`jnl`	Bounds all around: training energy-based models with bidirectional bounds. CoRR Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, Søren Hauberg
2021	A	`conf`	Geometrically Enriched Latent Spaces. AISTATS Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
2021	A*	`conf`	Hierarchical VAEs Know What They Don't Know. ICML Jakob Drachmann Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
2021	J	`jnl`	Hierarchical VAEs Know What They Don't Know. CoRR Jakob D. Havtorn, Jes Frellsen, Søren Hauberg, Lars Maaløe
2021	J	`jnl`	Intrinsic Grassmann Averages for Online Linear, Robust and Nonlinear Subspace Learning. IEEE Trans. Pattern Anal. Mach. Intell. Rudrasis Chakraborty, Liu Yang, Søren Hauberg, Baba C. Vemuri
2021	A*	`conf`	Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. ICML Martin Jørgensen, Søren Hauberg
2021	—	`conf`	Learning Riemannian Manifolds for Geodesic Motion Skills. Robotics: Science and Systems Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo
2021	J	`jnl`	Learning Riemannian Manifolds for Geodesic Motion Skills. CoRR Hadi Beik-Mohammadi, Søren Hauberg, Georgios Arvanitidis, Gerhard Neumann, Leonel Dario Rozo
2021	J	`jnl`	Multi-chart flows. CoRR Dimitris Kalatzis, Johan Ziruo Ye, Jesper Wohlert, Søren Hauberg
2021	J	`jnl`	Pulling back information geometry. CoRR Georgios Arvanitidis, Miguel González Duque, Alison Pouplin, Dimitris Kalatzis, Søren Hauberg
2021	—	`conf`	Spontaneous Symmetry Breaking in Data Visualization. ICANN (2) Cilie W. Feldager, Søren Hauberg, Lars Kai Hansen
2020	J	`jnl`	Bayesian Triplet Loss: Uncertainty Quantification in Image Retrieval. CoRR Frederik Warburg, Martin Jørgensen, Javier Civera, Søren Hauberg
2020	—	`conf`	Can You Trust Predictive Uncertainty Under Real Dataset Shifts in Digital Pathology? MICCAI (1) Jeppe Thagaard, Søren Hauberg, Bert van der Vegt, Thomas Ebstrup, Johan D. Hansen, Anders B. Dahl
2020	J	`jnl`	Geometrically Enriched Latent Spaces. CoRR Georgios Arvanitidis, Søren Hauberg, Bernhard Schölkopf
2020	J	`jnl`	Isometric Gaussian Process Latent Variable Model for Dissimilarity Data. CoRR Martin Jørgensen, Søren Hauberg
2020	A*	`conf`	Mapillary Street-Level Sequences: A Dataset for Lifelong Place Recognition. CVPR Frederik Warburg, Søren Hauberg, Manuel López-Antequera, Pau Gargallo, Yubin Kuang, Javier Civera
2020	J	`jnl`	Parallel SIAM J. Sci. Comput. Alfredo Buttari, Søren Hauberg, Costy Kodsi
2020	J	`jnl`	Probabilistic Spatial Transformers for Bayesian Data Augmentation. CoRR Pola Schwöbel, Frederik Warburg, Martin Jørgensen, Kristoffer H. Madsen, Søren Hauberg
2020	J	`jnl`	Reparametrization Invariance in non-parametric Causal Discovery. CoRR Martin Jørgensen, Søren Hauberg
2020	A*	`conf`	Variational Autoencoders with Riemannian Brownian Motion Priors. ICML Dimitrios Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
2020	J	`jnl`	Variational Autoencoders with Riemannian Brownian Motion Priors. CoRR Dimitris Kalatzis, David Eklund, Georgios Arvanitidis, Søren Hauberg
2020	J	`jnl`	What is a meaningful representation of protein sequences? CoRR Nicki Skafte Detlefsen, Søren Hauberg, Wouter Boomsma
2019	J	`jnl`	Expected path length on random manifolds. CoRR David Eklund, Søren Hauberg
2019	A*	`conf`	Explicit Disentanglement of Appearance and Perspective in Generative Models. NeurIPS Nicki Skafte Detlefsen, Søren Hauberg
2019	J	`jnl`	Explicit Disentanglement of Appearance and Perspective in Generative Models. CoRR Nicki Skafte Detlefsen, Søren Hauberg
2019	A	`conf`	Fast and Robust Shortest Paths on Manifolds Learned from Data. AISTATS Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober
2019	J	`jnl`	Fast and Robust Shortest Paths on Manifolds Learned from Data. CoRR Georgios Arvanitidis, Søren Hauberg, Philipp Hennig, Michael Schober
2019	A	`conf`	Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models. AISTATS Anton Mallasto, Søren Hauberg, Aasa Feragen
2019	A*	`conf`	Reliable training and estimation of variance networks. NeurIPS Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg
2019	J	`jnl`	Reliable training and estimation of variance networks. CoRR Nicki Skafte Detlefsen, Martin Jørgensen, Søren Hauberg
2018	A*	`conf`	Deep Diffeomorphic Transformer Networks. CVPR Nicki Skafte Detlefsen, Oren Freifeld, Søren Hauberg
2018	C	`conf`	Directional Statistics with the Spherical Normal Distribution. FUSION Søren Hauberg
2018	J	`jnl`	Geodesic Clustering in Deep Generative Models. CoRR Tao Yang, Georgios Arvanitidis, Dongmei Fu, Xiaogang Li, Søren Hauberg
2018	—	`conf`	Latent Space Oddity: on the Curvature of Deep Generative Models. ICLR (Poster) Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
2018	J	`jnl`	Only Bayes should learn a manifold (on the estimation of differential geometric structure from data). CoRR Søren Hauberg
2018	J	`jnl`	Probabilistic Riemannian submanifold learning with wrapped Gaussian process latent variable models. CoRR Anton Mallasto, Søren Hauberg, Aasa Feragen
2017	A*	`conf`	Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning. CVPR Rudrasis Chakraborty, Søren Hauberg, Baba C. Vemuri
2017	J	`jnl`	Intrinsic Grassmann Averages for Online Linear and Robust Subspace Learning. CoRR Rudrasis Chakraborty, Søren Hauberg, Baba C. Vemuri
2017	—	`conf`	Maximum Likelihood Estimation of Riemannian Metrics from Euclidean Data. GSI Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
2017	J	`jnl`	Transformations Based on Continuous Piecewise-Affine Velocity Fields. IEEE Trans. Pattern Anal. Mach. Intell. Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich, John W. Fisher III
2016	—	`conf`	A Locally Adaptive Normal Distribution. NIPS Georgios Arvanitidis, Lars Kai Hansen, Søren Hauberg
2016	J	`jnl`	Data-driven forward model inference for EEG brain imaging. NeuroImage Sofie Therese Hansen, Søren Hauberg, Lars Kai Hansen
2016	A	`conf`	Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation. AISTATS Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John W. Fisher III, Lars Kai Hansen
2016	A*	`conf`	Open Problem: Kernel methods on manifolds and metric spaces. What is the probability of a positive definite geodesic exponential kernel? COLT Aasa Feragen, Søren Hauberg
2016	J	`jnl`	Principal Curves on Riemannian Manifolds. IEEE Trans. Pattern Anal. Mach. Intell. Søren Hauberg
2016	J	`jnl`	Scalable Robust Principal Component Analysis Using Grassmann Averages. IEEE Trans. Pattern Anal. Mach. Intell. Søren Hauberg, Aasa Feragen, Raffi Enficiaud, Michael J. Black
2015	—	`conf`	A Random Riemannian Metric for Probabilistic Shortest-Path Tractography. MICCAI (1) Søren Hauberg, Michael Schober, Matthew G. Liptrot, Philipp Hennig, Aasa Feragen
2015	J	`jnl`	Dreaming More Data: Class-dependent Distributions over Diffeomorphisms for Learned Data Augmentation. CoRR Søren Hauberg, Oren Freifeld, Anders Boesen Lindbo Larsen, John W. Fisher III, Lars Kai Hansen
2015	A*	`conf`	Geodesic exponential kernels: When curvature and linearity conflict. CVPR Aasa Feragen, François Lauze, Søren Hauberg
2015	A*	`conf`	Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple. ICCV Oren Freifeld, Søren Hauberg, Kayhan N. Batmanghelich, John W. Fisher III
2014	J	`jnl`	Geodesic Exponential Kernels: When Curvature and Linearity Conflict. CoRR Aasa Feragen, François Lauze, Søren Hauberg
2014	A*	`conf`	Grassmann Averages for Scalable Robust PCA. CVPR Søren Hauberg, Aasa Feragen, Michael J. Black
2014	A	`conf`	Metrics for Probabilistic Geometries. UAI Alessandra Tosi, Søren Hauberg, Alfredo Vellido, Neil D. Lawrence
2014	J	`jnl`	Metrics for Probabilistic Geometries. CoRR Alessandra Tosi, Søren Hauberg, Alfredo Vellido, Neil D. Lawrence
2014	A*	`conf`	Model Transport: Towards Scalable Transfer Learning on Manifolds. CVPR Oren Freifeld, Søren Hauberg, Michael J. Black
2014	—	`conf`	Probabilistic Shortest Path Tractography in DTI Using Gaussian Process ODE Solvers. MICCAI (3) Michael Schober, Niklas Kasenburg, Aasa Feragen, Philipp Hennig, Søren Hauberg
2014	A	`conf`	Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics. AISTATS Philipp Hennig, Søren Hauberg
2013	J	`jnl`	Probabilistic Numerical Analysis in Riemannian Statistics. CoRR Philipp Hennig, Søren Hauberg
2013	J	`jnl`	Unscented Kalman Filtering on Riemannian Manifolds. J. Math. Imaging Vis. Søren Hauberg, François Lauze, Kim Steenstrup Pedersen
2012	—	`conf`	A Geometric take on Metric Learning. NIPS Søren Hauberg, Oren Freifeld, Michael J. Black
2012	J	`jnl`	Natural metrics and least-committed priors for articulated tracking. Image Vis. Comput. Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen
2012	—	`conf`	Spatial Measures between Human Poses for Classification and Understanding. AMDO Søren Hauberg, Kim Steenstrup Pedersen
2011	—	`conf`	An Empirical Study on the Performance of Spectral Manifold Learning Techniques. ICANN (1) Peter Mysling, Søren Hauberg, Kim Steenstrup Pedersen
2011	—	`conf`	Data-Driven Importance Distributions for Articulated Tracking. EMMCVPR Søren Hauberg, Kim Steenstrup Pedersen
2011	A*	`conf`	Means in spaces of tree-like shapes. ICCV Aasa Feragen, Søren Hauberg, Mads Nielsen, François Lauze
2011	J	`jnl`	Predicting Articulated Human Motion from Spatial Processes. Int. J. Comput. Vis. Søren Hauberg, Kim Steenstrup Pedersen
2011	—	`conf`	Unscented Kalman Filtering for Articulated Human Tracking. SCIA Anders Boesen Lindbo Larsen, Søren Hauberg, Kim Steenstrup Pedersen
2010	—	`conf`	GPU Accelerated Likelihoods for Stereo-Based Articulated Tracking. ECCV Workshops (1) Rune Møllegaard Friborg, Søren Hauberg, Kenny Erleben
2010	—	`conf`	Gaussian-Like Spatial Priors for Articulated Tracking. ECCV (1) Søren Hauberg, Stefan Sommer, Kim Steenstrup Pedersen
2010	—	`conf`	Manifold Valued Statistics, Exact Principal Geodesic Analysis and the Effect of Linear Approximations. ECCV (6) Stefan Sommer, François Lauze, Søren Hauberg, Mads Nielsen
2010	—	`conf`	Stick It! Articulated Tracking Using Spatial Rigid Object Priors. ACCV (3) Søren Hauberg, Kim Steenstrup Pedersen
2009	—	`conf`	Interactive Inverse Kinematics for Human Motion Estimation. VRIPHYS Morten Engell-Nørregård, Søren Hauberg, Jérôe Lapuyade, Kenny Erleben, Kim Steenstrup Pedersen
2009	—	`conf`	Three Dimensional Monocular Human Motion Analysis in End-Effector Space. EMMCVPR Søren Hauberg, Jérôe Lapuyade, Morten Engell-Nørregård, Kenny Erleben, Kim Steenstrup Pedersen
2008	J	`jnl`	An Efficient Algorithm for Modelling Duration in Hidden Markov Models, with a Dramatic Application. J. Math. Imaging Vis. Søren Hauberg, Jakob Sloth
2008	J	`jnl`	Brownian Warps for Non-Rigid Registration. J. Math. Imaging Vis. Mads Nielsen, Peter Johansen, Andrew D. Jackson, Benny Lautrup, Søren Hauberg